Geneticist, Obstetrician & Gynecologist (OB/GYN), Pediatrician
15 years of experience
Video profile
Accepting new patients
5323 Harry Hines Blvd
Northwest Dallas, Dallas, TX 75390
214-648-3113
Locations and availability (3)

Education ?

Medical School Score
The University of Texas Southwestern (1995)
  • Currently 1 of 4 apples

Awards & Distinctions ?

Awards  
Texas Medical Association Alternate Student Representative on Perinatal Health (1995) Class of 1995, Class Officer (1995) Wyeth Resident Reporter (1998) Dallas Area Breastfeeding Alliance (2007)
Castle Connolly's Top Doctors™ (2013)
Patients' Choice Award (2012)
Compassionate Doctor Recognition (2012)
Top Ten Doctors (2012)
Obstetrics and Gynecology, Lovefield West, Dallas, TX
Castle Connolly Top Doctors: Texas™ (2009)

Affiliations ?

Dr. Lo is affiliated with 16 hospitals.

Hospital Affilations

Score

Rankings

  • UT Southwestern University Hospital - Zale Lipshy
    5151 Harry Hines Blvd, Dallas, TX 75235
    • Currently 4 of 4 crosses
    Top 25%
  • UT Southwestern University Hospital - St. Paul
    5909 Harry Hines Blvd, Dallas, TX 75235
    • Currently 4 of 4 crosses
    Top 25%
  • Texas Health Presbyterian Hospital Plano
    6200 W Parker Rd, Plano, TX 75093
    • Currently 4 of 4 crosses
    Top 25%
  • Children's Medical Center of Dallas
    Obstetrician & Gynecologist
    1935 Motor St, Dallas, TX 75235
    • Currently 3 of 4 crosses
    Top 50%
  • Texas Health Presbyterian Hospital Allen
    1105 Central Expy N, Allen, TX 75013
    • Currently 3 of 4 crosses
    Top 50%
  • Medical Center Of Plano
    3901 W 15th St, Plano, TX 75075
    • Currently 2 of 4 crosses
  • Centennial Medical Center
    12505 Lebanon Rd, Frisco, TX 75035
    • Currently 2 of 4 crosses
  • Baylor Medical Center at Carrollton
    4343 N Josey Ln, Carrollton, TX 75010
    • Currently 2 of 4 crosses
  • Parkland Health & Hospital System
    5201 Harry Hines Blvd, Dallas, TX 75235
    • Currently 1 of 4 crosses
  • UT Southwestern Zale Lipshy Hospital
  • UT Southwestern St Paul Hospital
  • Texas Health Plano
  • UT Southwestern Medical Center at Dallas *
  • University Hospital - St Paul
  • Harris Methodist - Springwood
    1608 Hospital Pkwy, Bedford, TX 76022
  • Texas Health Allen
  • * This information was reported to Vitals by the doctor or doctor's office.

    Publications & Research

    Dr. Lo has contributed to 89 publications.
    Title Mutual Information-based Template Matching Scheme for Detection of Breast Masses: from Mammography to Digital Breast Tomosynthesis.
    Date April 2012
    Journal Journal of Biomedical Informatics
    Excerpt

    Development of a computational decision aid for a new medical imaging modality typically is a long and complicated process. It consists of collecting data in the form of images and annotations, development of image processing and pattern recognition algorithms for analysis of the new images and finally testing of the resulting system. Since new imaging modalities are developed more rapidly than ever before, any effort for decreasing the time and cost of this development process could result in maximizing the benefit of the new imaging modality to patients by making the computer aids quickly available to radiologists that interpret the images. In this paper, we make a step in this direction and investigate the possibility of translating the knowledge about the detection problem from one imaging modality to another. Specifically, we present a computer-aided detection (CAD) system for mammographic masses that uses a mutual information-based template matching scheme with intelligently selected templates. We presented principles of template matching with mutual information for mammography before. In this paper, we present an implementation of those principles in a complete computer-aided detection system. The proposed system, through an automatic optimization process, chooses the most useful templates (mammographic regions of interest) using a large database of previously collected and annotated mammograms. Through this process, the knowledge about the task of detecting masses in mammograms is incorporated in the system. Then, we evaluate whether our system developed for screen-film mammograms can be successfully applied not only to other mammograms but also to digital breast tomosynthesis (DBT) reconstructed slices without adding any DBT cases for training. Our rationale is that since mutual information is known to be a robust inter-modality image similarity measure, it has high potential of transferring knowledge between modalities in the context of the mass detection task. Experimental evaluation of the system on mammograms showed competitive performance compared to other mammography CAD systems recently published in the literature. When the system was applied "as-is" to DBT, its performance was notably worse than that for mammograms. However, with a simple additional preprocessing step, the performance of the system reached levels similar to that obtained for mammograms. In conclusion, the presented CAD system not only performed competitively on screen-film mammograms but it also performed robustly on DBT showing that direct transfer of knowledge across breast imaging modalities for mass detection is in fact possible.

    Title Breast Tomosynthesis: State-of-the-art and Review of the Literature.
    Date January 2012
    Journal Academic Radiology
    Title Knowledge-based Imrt Treatment Planning for Prostate Cancer.
    Date August 2011
    Journal Medical Physics
    Excerpt

    To demonstrate the feasibility of using a knowledge base of prior treatment plans to generate new prostate intensity modulated radiation therapy (IMRT) plans. Each new case would be matched against others in the knowledge base. Once the best match is identified, that clinically approved plan is used to generate the new plan.

    Title Complete Sequencing of Pndm-hk Encoding Ndm-1 Carbapenemase from a Multidrug-resistant Escherichia Coli Strain Isolated in Hong Kong.
    Date August 2011
    Journal Plos One
    Excerpt

    The emergence of plasmid-mediated carbapenemases, such as NDM-1 in Enterobacteriaceae is a major public health issue. Since they mediate resistance to virtually all β-lactam antibiotics and there is often co-resistance to other antibiotic classes, the therapeutic options for infections caused by these organisms are very limited.

    Title Comparative Performance of Multiview Stereoscopic and Mammographic Display Modalities for Breast Lesion Detection.
    Date June 2011
    Journal Medical Physics
    Excerpt

    Mammography is known to be one of the most difficult radiographic exams to interpret. Mammography has important limitations, including the superposition of normal tissue that can obscure a mass, chance alignment of normal tissue to mimic a true lesion and the inability to derive volumetric information. It has been shown that stereomammography can overcome these deficiencies by showing that layers of normal tissue lay at different depths. If standard stereomammography (i.e., a single stereoscopic pair consisting of two projection images) can significantly improve lesion detection, how will multiview stereoscopy (MVS), where many projection images are used, compare to mammography? The aim of this study was to assess the relative performance of MVS compared to mammography for breast mass detection.

    Title Computer-aided Classification of Breast Masses: Performance and Interobserver Variability of Expert Radiologists Versus Residents.
    Date January 2011
    Journal Radiology
    Excerpt

    To evaluate the interobserver variability in descriptions of breast masses by dedicated breast imagers and radiology residents and determine how any differences in lesion description affect the performance of a computer-aided diagnosis (CAD) computer classification system.

    Title Efficient Fourier-wavelet Super-resolution.
    Date January 2011
    Journal Ieee Transactions on Image Processing : a Publication of the Ieee Signal Processing Society
    Excerpt

    Super-resolution (SR) is the process of combining multiple aliased low-quality images to produce a high-resolution high-quality image. Aside from registration and fusion of low-resolution images, a key process in SR is the restoration and denoising of the fused images. We present a novel extension of the combined Fourier-wavelet deconvolution and denoising algorithm ForWarD to the multiframe SR application. Our method first uses a fast Fourier-base multiframe image restoration to produce a sharp, yet noisy estimate of the high-resolution image. Our method then applies a space-variant nonlinear wavelet thresholding that addresses the nonstationarity inherent in resolution-enhanced fused images. We describe a computationally efficient method for implementing this space-variant processing that leverages the efficiency of the fast Fourier transform (FFT) to minimize complexity. Finally, we demonstrate the effectiveness of this algorithm for regular imagery as well as in digital mammography.

    Title A Low-cost, Portable, and Quantitative Spectral Imaging System for Application to Biological Tissues.
    Date November 2010
    Journal Optics Express
    Excerpt

    The ability of diffuse reflectance spectroscopy to extract quantitative biological composition of tissues has been used to discern tissue types in both pre-clinical and clinical cancer studies. Typically, diffuse reflectance spectroscopy systems are designed for single-point measurements. Clinically, an imaging system would provide valuable spatial information on tissue composition. While it is feasible to build a multiplexed fiber-optic probe based spectral imaging system, these systems suffer from drawbacks with respect to cost and size. To address these we developed a compact and low cost system using a broadband light source with an 8-slot filter wheel for illumination and silicon photodiodes for detection. The spectral imaging system was tested on a set of tissue mimicking liquid phantoms which yielded an optical property extraction accuracy of 6.40 +/- 7.78% for the absorption coefficient (micro(a)) and 11.37 +/- 19.62% for the wavelength-averaged reduced scattering coefficient (micro(s)').

    Title A Technique Optimization Protocol and the Potential for Dose Reduction in Digital Mammography.
    Date May 2010
    Journal Medical Physics
    Excerpt

    Digital mammography requires revisiting techniques that have been optimized for prior screen/film mammography systems. The objective of the study was to determine optimized radiographic technique for a digital mammography system and demonstrate the potential for dose reduction in comparison to the clinically established techniques based on screen- film. An objective figure of merit (FOM) was employed to evaluate a direct-conversion amorphous selenium (a-Se) FFDM system (Siemens Mammomat Novation(DR), Siemens AG Medical Solutions, Erlangen, Germany) and was derived from the quotient of the squared signal-difference-to-noise ratio to mean glandular dose, for various combinations of technique factors and breast phantom configurations including kilovoltage settings (23-35 kVp), target/filter combinations (Mo-Mo and W-Rh), breast-equivalent plastic in various thicknesses (2-8 cm) and densities (100% adipose, 50% adipose/50% glandular, and 100% glandular), and simulated mass and calcification lesions. When using a W-Rh spectrum, the optimized FOM results for the simulated mass and calcification lesions showed highly consistent trends with kVp for each combination of breast density and thickness. The optimized kVp ranged from 26 kVp for 2 cm 100% adipose breasts to 30 kVp for 8 cm 100% glandular breasts. The use of the optimized W-Rh technique compared to standard Mo-Mo techniques provided dose savings ranging from 9% for 2 cm thick, 100% adipose breasts, to 63% for 6 cm thick, 100% glandular breasts, and for breasts with a 50% adipose/50% glandular composition, from 12% for 2 cm thick breasts up to 57% for 8 cm thick breasts.

    Title The Quantitative Potential for Breast Tomosynthesis Imaging.
    Date May 2010
    Journal Medical Physics
    Excerpt

    Due to its limited angular scan range, breast tomosynthesis has lower resolution in the depth direction, which may limit its accuracy in quantifying tissue density. This study assesses the quantitative potential of breast tomosynthesis using relatively simple reconstruction and image processing algorithms. This quantitation could allow improved characterization of lesions as well as image processing to present tomosynthesis images with the familiar appearance of mammography by preserving more low-frequency information.

    Title Loop Electrosurgical Excision Procedure and Risk of Preterm Birth.
    Date March 2010
    Journal Obstetrics and Gynecology
    Excerpt

    To examine whether preterm birth is related to the loop electrosurgical excision procedure (LEEP) itself or intrinsic to the women undergoing the procedure.

    Title Prediction of Diabetes Recurrence in Women with Class A1 (diet-treated) Gestational Diabetes.
    Date March 2010
    Journal American Journal of Perinatology
    Excerpt

    We sought to evaluate the likelihood of recurrent diabetes in women with a prior history of diet-treated (class A(1)) gestational diabetes mellitus (GDM). In a retrospective cohort analysis, nulliparous women diagnosed based upon National Diabetes Data Group criteria with diet-treated GDM who had recurrent diabetes in a subsequent pregnancy were compared with those who did not have recurrent diabetes. The probability of recurrent diabetes was calculated using maternal age at first pregnancy, interpregnancy interval, and body mass index (BMI) during the subsequent pregnancy. Three hundred forty-four nulliparous women with diet-treated GDM had a subsequent delivery in our database. One hundred thirty-seven (40%) had recurrent diabetes. Women with a history of GDM were more likely to have recurrent diabetes if they were heavier (193 versus 173 lbs; P < 0.001; BMI 35.7 versus 32.2; P < 0.001) and waited longer between pregnancies (2.9 versus 2.4 years, P = 0.02). Age, interpregnancy interval, and BMI can be used to predict diabetes recurrence in pregnant women with a history of GDM.

    Title Antimicrobial Resistance Among Uropathogens That Cause Acute Uncomplicated Cystitis in Women in Hong Kong: a Prospective Multicenter Study in 2006 to 2008.
    Date February 2010
    Journal Diagnostic Microbiology and Infectious Disease
    Excerpt

    A prospective multicenter study was conducted to assess the epidemiology of antimicrobial resistance among uropathogens causing uncomplicated cystitis. Adult women with clinical diagnosis of uncomplicated cystitis were enrolled from 54 participating centers distributed all over Hong Kong during 2006 to 2008. A positive urine culture was found in 59.5% (352/592) patients. The patients had mean age of 44.9 years, and most (89.2%) were otherwise healthy. The most prevalent causative organism was Escherichia coli (77%), followed by other Enterobacteriaceae (14.2%), staphylococci (5.1%), and other Gram-positive bacteria (3.7%). The resistance rates of E. coli to co-trimoxazole and ciprofloxacin were 29.5% and 12.9%, respectively, and 14 isolates (5.2%) were confirmed as extended-spectrum beta-lactamase (ESBL) producers. Of the ESBL producers, molecular studies showed CTX-M-14, CTX-M-24, or CTX-M-9. Nitrofurantoin and fosfomycin were active against >90% of the isolates, regardless of resistance phenotypes for other drugs. Pulsed-field gel electrophoresis of representative isolates showed that the antibiotic-resistant strains were genetically diverse. Patients with history of recent antibiotic use were significantly more likely to have infection by E. coli with co-trimoxazole resistance (odds ratio [OR], 2.8; 95% confidence interval [CI], 1.4-5.7; P = 0.003) and ciprofloxacin resistance (OR, 2.5; 95% CI, 1.1-5.8; P = 0.03). Knowledge of the resistance data and risk factors could inform better use of antibiotics for empiric therapy for acute uncomplicated cystitis.

    Title Optimized Image Acquisition for Breast Tomosynthesis in Projection and Reconstruction Space.
    Date January 2010
    Journal Medical Physics
    Excerpt

    Breast tomosynthesis has been an exciting new development in the field of breast imaging. While the diagnostic improvement via tomosynthesis is notable, the full potential of tomosynthesis has not yet been realized. This may be attributed to the dependency of the diagnostic quality of tomosynthesis on multiple variables, each of which needs to be optimized. Those include dose, number of angular projections, and the total angular span of those projections. In this study, the authors investigated the effects of these acquisition parameters on the overall diagnostic image quality of breast tomosynthesis in both the projection and reconstruction space. Five mastectomy specimens were imaged using a prototype tomosynthesis system. 25 angular projections of each specimen were acquired at 6.2 times typical single-view clinical dose level. Images at lower dose levels were then simulated using a noise modification routine. Each projection image was supplemented with 84 simulated 3 mm 3D lesions embedded at the center of 84 nonoverlapping ROIs. The projection images were then reconstructed using a filtered backprojection algorithm at different combinations of acquisition parameters to investigate which of the many possible combinations maximizes the performance. Performance was evaluated in terms of a Laguerre-Gauss channelized Hotelling observer model-based measure of lesion detectability. The analysis was also performed without reconstruction by combining the model results from projection images using Bayesian decision fusion algorithm. The effect of acquisition parameters on projection images and reconstructed slices were then compared to derive an optimization rule for tomosynthesis. The results indicated that projection images yield comparable but higher performance than reconstructed images. Both modes, however, offered similar trends: Performance improved with an increase in the total acquisition dose level and the angular span. Using a constant dose level and angular span, the performance rolled off beyond a certain number of projections, indicating that simply increasing the number of projections in tomosynthesis may not necessarily improve its performance. The best performance for both projection images and tomosynthesis slices was obtained for 15-17 projections spanning an angular are of approximately 45 degrees--the maximum tested in our study, and for an acquisition dose equal to single-view mammography. The optimization framework developed in this framework is applicable to other reconstruction techniques and other multiprojection systems.

    Title Application of Likelihood Ratio to Classification of Mammographic Masses; Performance Comparison to Case-based Reasoning.
    Date November 2009
    Journal Medical Physics
    Excerpt

    The likelihood ratio (LR) is an optimal approach for deciding which of two alternate hypotheses best describes a given situation. We adopted this formalism for predicting whether biopsy results of mammographic masses will be benign or malignant, aiming to reduce the number of biopsies performed on benign lesions. We compared the performance of this LR-based algorithm (LRb) to a case-based reasoning (CBR) classifier, which provides a solution to a new problem using past similiar cases. Each classifier used mammographers' BI-RADS descriptions of mammographic masses as input. The database consisted of 646 biopsy-proven mammography cases. Performance was evaluated using Receiver Operating Characteristic (ROC) analysis, Round Robin sampling, and bootstrap. The ROC areas (AUC) for the LRb and CBR were 0.91+/- 0.01 and 0.92 +/- 0.01, respectively. The partial ROC area index (0.90AUC) was the same for both classifiers, 0.59 +/- 0.05. At a sensitivity of 98%, the CBR would spare 204 (49%) of benign lesions from biopsy; the LRb would spare 209 (51%) benign lesions. The performance of the two classifiers was very similar, with no statistical differences in AUC or 0.90AUC. Although the CBR and LRb originate from different fields of study, their implementations differ only in the estimation of the probability density functions (PDFs) of the feature distributions. The CBR performs this estimation implicitly, while using various similarity metrics. On the other hand, the estimation of the PDFs is specified explicitly in the LRb implementation. This difference in the estimation of the PDFs results in the very small difference in performance, and at 98% sensitivity, both classifiers would spare about half of the benign mammographic masses from biopsy. The CBR and LRb are equivalent methods in implementation and performance.

    Title Oxa-23-type Imipenem Resistance in Acinetobacter Baumannii in Hong Kong.
    Date October 2009
    Journal International Journal of Antimicrobial Agents
    Title Varibaculum Cambriense Infections in Hong Kong, China, 2006.
    Date September 2009
    Journal Emerging Infectious Diseases
    Title Do Serum Biomarkers Really Measure Breast Cancer?
    Date July 2009
    Journal Bmc Cancer
    Excerpt

    Because screening mammography for breast cancer is less effective for premenopausal women, we investigated the feasibility of a diagnostic blood test using serum proteins.

    Title Weekly Compared with Daily Blood Glucose Monitoring in Women with Diet-treated Gestational Diabetes.
    Date June 2009
    Journal Obstetrics and Gynecology
    Excerpt

    To estimate whether daily blood glucose self-monitoring reduces macrosomia when compared with weekly office testing in women with gestational diabetes.

    Title Can Compression Be Reduced for Breast Tomosynthesis? Monte Carlo Study on Mass and Microcalcification Conspicuity in Tomosynthesis.
    Date June 2009
    Journal Radiology
    Excerpt

    To assess, in a voxelized anthropomorphic breast phantom, how the conspicuity of breast masses and microcalcifications may be affected by applying reduced breast compression in tomosynthesis.

    Title A Strategy for Quantitative Spectral Imaging of Tissue Absorption and Scattering Using Light Emitting Diodes and Photodiodes.
    Date June 2009
    Journal Optics Express
    Excerpt

    A diffuse reflectance spectroscopy system was modified as a step towards miniaturization and spectral imaging of tissue absorption and scattering. The modified system uses a tunable source and an optical fiber for illumination and a photodiode in contact with tissue for detection. Compared to the previous system, it is smaller, less costly, and has comparable performance in extracting optical properties in tissue phantoms. Wavelength reduction simulations show the feasibility of replacing the source with LEDs to further decrease system size and cost. Simulated crosstalk analysis indicates that this evolving system can be multiplexed for spectral imaging in the future.

    Title Towards Optimized Acquisition Scheme for Multiprojection Correlation Imaging of Breast Cancer.
    Date May 2009
    Journal Academic Radiology
    Excerpt

    Correlation imaging (CI) is a form of multiprojection imaging in which multiple images of a patient are acquired from slightly different angles. Information from these images is combined to make the final diagnosis. A critical factor affecting the performance of CI is its data acquisition scheme, because nonoptimized acquisition may distort pathologic indicators. The authors describe a computer-aided detection (CADe) methodology to optimize the acquisition scheme of CI for superior diagnostic accuracy.

    Title Cost-effective Diffuse Reflectance Spectroscopy Device for Quantifying Tissue Absorption and Scattering in Vivo.
    Date March 2009
    Journal Journal of Biomedical Optics
    Excerpt

    A hybrid optical device that uses a multimode fiber coupled to a tunable light source for illumination and a 2.4-mm photodiode for detection in contact with the tissue surface is developed as a first step toward our goal of developing a cost-effective, miniature spectral imaging device to map tissue optical properties in vivo. This device coupled with an inverse Monte Carlo model of reflectance is demonstrated to accurately quantify tissue absorption and scattering in tissue-like turbid synthetic phantoms with a wide range of optical properties. The overall errors for quantifying the absorption and scattering coefficients are 6.0+/-5.6 and 6.1+/-4.7%, respectively. Compared with fiber-based detection, having the detector right at the tissue surface can significantly improve light collection efficiency, thus reducing the requirement for sophisticated detectors with high sensitivity, and this design can be easily expanded into a quantitative spectral imaging system for mapping tissue optical properties in vivo.

    Title Automated Breast Mass Detection in 3d Reconstructed Tomosynthesis Volumes: a Featureless Approach.
    Date November 2008
    Journal Medical Physics
    Excerpt

    The purpose of this study was to propose and implement a computer aided detection (CADe) tool for breast tomosynthesis. This task was accomplished in two stages-a highly sensitive mass detector followed by a false positive (FP) reduction stage. Breast tomosynthesis data from 100 human subject cases were used, of which 25 subjects had one or more mass lesions and the rest were normal. For stage 1, filter parameters were optimized via a grid search. The CADe identified suspicious locations were reconstructed to yield 3D CADe volumes of interest. The first stage yielded a maximum sensitivity of 93% with 7.7 FPs/breast volume. Unlike traditional CADe algorithms in which the second stage FP reduction is done via feature extraction and analysis, instead information theory principles were used with mutual information as a similarity metric. Three schemes were proposed, all using leave-one-case-out cross validation sampling. The three schemes, A, B, and C, differed in the composition of their knowledge base of regions of interest (ROIs). Scheme A's knowledge base was comprised of all the mass and FP ROIs generated by the first stage of the algorithm. Scheme B had a knowledge base that contained information from mass ROIs and randomly extracted normal ROIs. Scheme C had information from three sources of information-masses, FPs, and normal ROIs. Also, performance was assessed as a function of the composition of the knowledge base in terms of the number of FP or normal ROIs needed by the system to reach optimal performance. The results indicated that the knowledge base needed no more than 20 times as many FPs and 30 times as many normal ROIs as masses to attain maximal performance. The best overall system performance was 85% sensitivity with 2.4 FPs per breast volume for scheme A, 3.6 FPs per breast volume for scheme B, and 3 FPs per breast volume for scheme C.

    Title Optimization of Exposure Parameters in Full Field Digital Mammography.
    Date September 2008
    Journal Medical Physics
    Excerpt

    Optimization of exposure parameters (target, filter, and kVp) in digital mammography necessitates maximization of the image signal-to-noise ratio (SNR), while simultaneously minimizing patient dose. The goal of this study is to compare, for each of the major commercially available full field digital mammography (FFDM) systems, the impact of the selection of technique factors on image SNR and radiation dose for a range of breast thickness and tissue types. This phantom study is an update of a previous investigation and includes measurements on recent versions of two of the FFDM systems discussed in that article, as well as on three FFDM systems not available at that time. The five commercial FFDM systems tested, the Senographe 2000D from GE Healthcare, the Mammomat Novation DR from Siemens, the Selenia from Hologic, the Fischer Senoscan, and Fuji's 5000MA used with a Lorad M-IV mammography unit, are located at five different university test sites. Performance was assessed using all available x-ray target and filter combinations and nine different phantom types (three compressed thicknesses and three tissue composition types). Each phantom type was also imaged using the automatic exposure control (AEC) of each system to identify the exposure parameters used under automated image acquisition. The figure of merit (FOM) used to compare technique factors is the ratio of the square of the image SNR to the mean glandular dose. The results show that, for a given target/filter combination, in general FOM is a slowly changing function of kVp, with stronger dependence on the choice of target/filter combination. In all cases the FOM was a decreasing function of kVp at the top of the available range of kVp settings, indicating that higher tube voltages would produce no further performance improvement. For a given phantom type, the exposure parameter set resulting in the highest FOM value was system specific, depending on both the set of available target/filter combinations, and on the receptor type. In most cases, the AECs of the FFDM systems successfully identified exposure parameters resulting in FOM values near the maximum ones, however, there were several examples where AEC performance could be improved.

    Title Training Neural Network Classifiers for Medical Decision Making: the Effects of Imbalanced Datasets on Classification Performance.
    Date July 2008
    Journal Neural Networks : the Official Journal of the International Neural Network Society
    Excerpt

    This study investigates the effect of class imbalance in training data when developing neural network classifiers for computer-aided medical diagnosis. The investigation is performed in the presence of other characteristics that are typical among medical data, namely small training sample size, large number of features, and correlations between features. Two methods of neural network training are explored: classical backpropagation (BP) and particle swarm optimization (PSO) with clinically relevant training criteria. An experimental study is performed using simulated data and the conclusions are further validated on real clinical data for breast cancer diagnosis. The results show that classifier performance deteriorates with even modest class imbalance in the training data. Further, it is shown that BP is generally preferable over PSO for imbalanced training data especially with small data sample and large number of features. Finally, it is shown that there is no clear preference between oversampling and no compensation approach and some guidance is provided regarding a proper selection.

    Title Dedicated Breast Computed Tomography: Volume Image Denoising Via a Partial-diffusion Equation Based Technique.
    Date July 2008
    Journal Medical Physics
    Excerpt

    Dedicated breast computed tomography (CT) imaging possesses the potential for improved lesion detection over conventional mammograms, especially for women with dense breasts. The breast CT images are acquired with a glandular dose comparable to that of standard two-view mammography for a single breast. Due to dose constraints, the reconstructed volume has a non-negligible quantum noise when thin section CT slices are visualized. It is thus desirable to reduce noise in the reconstructed breast volume without loss of spatial resolution. In this study, partial diffusion equation (PDE) based denoising techniques specifically for breast CT were applied at different steps along the reconstruction process and it was found that denoising performed better when applied to the projection data rather than reconstructed data. Simulation results from the contrast detail phantom show that the PDE technique outperforms Wiener denoising as well as adaptive trimmed mean filter. The PDE technique increases its performance advantage relative to Wiener techniques when the photon fluence is reduced. With the PDE technique, the sensitivity for lesion detection using the contrast detail phantom drops by less than 7% when the dose is cut down to 40% of the two-view mammography. For subjective evaluation, the PDE technique was applied to two human subject breast data sets acquired on a prototype breast CT system. The denoised images had appealing visual characteristics with much lower noise levels and improved tissue textures while maintaining sharpness of the original reconstructed volume.

    Title Neutron-stimulated Emission Computed Tomography of a Multi-element Phantom.
    Date July 2008
    Journal Physics in Medicine and Biology
    Excerpt

    This paper describes the implementation of neutron-stimulated emission computed tomography (NSECT) for non-invasive imaging and reconstruction of a multi-element phantom. The experimental apparatus and process for acquisition of multi-spectral projection data are described along with the reconstruction algorithm and images of the two elements in the phantom. Independent tomographic reconstruction of each element of the multi-element phantom was performed successfully. This reconstruction result is the first of its kind and provides encouraging proof of concept for proposed subsequent spectroscopic tomography of biological samples using NSECT.

    Title A Mathematical Model Platform for Optimizing a Multiprojection Breast Imaging System.
    Date June 2008
    Journal Medical Physics
    Excerpt

    Multiprojection imaging is a technique in which a plurality of digital radiographic images of the same patient are acquired within a short interval of time from slightly different angles. Information from each image is combined to determine the final diagnosis. Projection data are either reconstructed into slices as in the case of tomosynthesis or analyzed directly as in the case of multiprojection correlation imaging technique, thereby avoiding reconstruction artifacts. In this study, the authors investigated the optimum geometry of acquisitions of a multiprojection breast correlation imaging system in terms of the number of projections and their total angular span that yield maximum performance in a task that models clinical decision. Twenty-five angular projections of each breast from 82 human subjects in our breast tomosynthesis database were each supplemented with a simulated 3 mm mass. An approach based on Laguerre-Gauss channelized Hotelling observer was developed to assess the detectability of the mass in terms of receiver operating characteristic (ROC) curves. Two methodologies were developed to integrate results from individual projections into one combined ROC curve as the overall figure of merit. To optimize the acquisition geometry, different components of acquisitions were changed to investigate which one of the many possible configurations maximized the area under the combined ROC curve. Optimization was investigated under two acquisition dose conditions corresponding to a fixed total dose delivered to the patient and a variable dose condition, based on the number of projections used. In either case, the detectability was dependent on the number of projections used, the total angular span of those projections, and the acquisition dose level. In the first case, the detectability approximately followed a bell curve as a function of the number of projections with the maximum between 8 and 16 projections spanning angular arcs of about 23 degrees-45 degrees, respectively. In the second case, the detectability increased with the number of projections approaching an asymptote at 11-17 projections for an angular span of about 45 degrees. These results indicate the inherent information content of the multi-projection image data reflecting the relative role of quantum and anatomical noise in multiprojection breast imaging. The optimization scheme presented here may be applied to any multiprojection imaging modalities and may be extended by including reconstruction in the case of digital breast tomosynthesis and breast computed tomography.

    Title Point/counterpoint. Cone Beam X-ray Ct Will Be Superior to Digital X-ray Tomosynthesis in Imaging the Breast and Delineating Cancer.
    Date April 2008
    Journal Medical Physics
    Title Diet-treated Gestational Diabetes Mellitus: Comparison of Early Vs Routine Diagnosis.
    Date April 2008
    Journal American Journal of Obstetrics and Gynecology
    Excerpt

    OBJECTIVE: The purpose of this study was to compare pregnancy outcomes in women with diet-treated gestational diabetes mellitus (GDM) that was diagnosed at < 24 weeks of gestation to those women who received the diagnosis at > or = 24 weeks of gestation. STUDY DESIGN: This was a retrospective cohort study of 2596 women with diet-treated GDM who delivered between December 1999 and June 2005 at Parkland Hospital. Women with risk factors for GDM underwent immediate glucose screening; women without risk factors underwent universal glucose screening between 24 and 28 weeks of gestation. Women with diet-treated GDM that was diagnosed at < 24 weeks of gestation (n = 339; 13.1%) were compared with those women who received the diagnosis at > or = 24 weeks of gestation. RESULTS: Women with an earlier diagnosis of diet-treated GDM were at increased risk of preeclampsia and the delivery of large infants. Even after adjustment for differences in maternal characteristics and glycemic control, the risk of preeclampsia persisted (odds ratio, 2.4; 95% CI, 1.5, 3.8). CONCLUSION: Women with an early diagnosis of diet-treated GDM have a 2-fold increased risk of preeclampsia.

    Title Importance of Point-by-point Back Projection Correction for Isocentric Motion in Digital Breast Tomosynthesis: Relevance to Morphology of Structures Such As Microcalcifications.
    Date December 2007
    Journal Medical Physics
    Excerpt

    Digital breast tomosynthesis is a three-dimensional imaging technique that provides an arbitrary set of reconstruction planes in the breast from a limited-angle series of projection images acquired while the x-ray tube moves. Traditional shift-and-add (SAA) tomosynthesis reconstruction is a common mathematical method to line up each projection image based on its shifting amount to generate reconstruction slices. With parallel-path geometry of tube motion, the path of the tube lies in a plane parallel to the plane of the detector. The traditional SAA algorithm gives shift amounts for each projection image calculated only along the direction of x-ray tube movement. However, with the partial isocentric motion of the x-ray tube in breast tomosynthesis, small objects such as microcalcifications appear blurred (for instance, about 1-4 pixels in blur for a microcalcification in a human breast) in traditional SAA images in the direction perpendicular to the direction of tube motion. Some digital breast tomosynthesis algorithms reported in the literature utilize a traditional one-dimensional SAA method that is not wholly suitable for isocentric motion. In this paper, a point-by-point back projection (BP) method is described and compared with traditional SAA for the important clinical task of evaluating morphology of small objects such as microcalcifications. Impulse responses at different three-dimensional locations with five different combinations of imaging acquisition parameters were investigated. Reconstruction images of microcalcifications in a human subject were also evaluated. Results showed that with traditional SAA and 45 degrees view angle of tube movement with respect to the detector, at the same height above the detector, the in-plane blur artifacts were obvious for objects farther away from x-ray source. In a human subject, the appearance of calcifications was blurred in the direction orthogonal to the tube motion with traditional SAA. With point-by-point BP, the appearance of calcifications was sharper. The point-by-point BP method demonstrated improved rendition of microcalcifications in the direction perpendicular to the tube motion direction. With wide angles or for imaging of larger breasts, this point-by-point BP rather than the traditional SAA should also be considered as the basis of further deblurring algorithms that work in conjunction with the BP method.

    Title Information-theoretic Cad System in Mammography: Entropy-based Indexing for Computational Efficiency and Robust Performance.
    Date October 2007
    Journal Medical Physics
    Excerpt

    We have previously presented a knowledge-based computer-assisted detection (KB-CADe) system for the detection of mammographic masses. The system is designed to compare a query mammographic region with mammographic templates of known ground truth. The templates are stored in an adaptive knowledge database. Image similarity is assessed with information theoretic measures (e.g., mutual information) derived directly from the image histograms. A previous study suggested that the diagnostic performance of the system steadily improves as the knowledge database is initially enriched with more templates. However, as the database increases in size, an exhaustive comparison of the query case with each stored template becomes computationally burdensome. Furthermore, blind storing of new templates may result in redundancies that do not necessarily improve diagnostic performance. To address these concerns we investigated an entropy-based indexing scheme for improving the speed of analysis and for satisfying database storage restrictions without compromising the overall diagnostic performance of our KB-CADe system. The indexing scheme was evaluated on two different datasets as (i) a search mechanism to sort through the knowledge database, and (ii) a selection mechanism to build a smaller, concise knowledge database that is easier to maintain but still effective. There were two important findings in the study. First, entropy-based indexing is an effective strategy to identify fast a subset of templates that are most relevant to a given query. Only this subset could be analyzed in more detail using mutual information for optimized decision making regarding the query. Second, a selective entropy-based deposit strategy may be preferable where only high entropy cases are maintained in the knowledge database. Overall, the proposed entropy-based indexing scheme was shown to reduce the computational cost of our KB-CADe system by 55% to 80% while maintaining the system's diagnostic performance.

    Title Breast Mass Lesions: Computer-aided Diagnosis Models with Mammographic and Sonographic Descriptors.
    Date September 2007
    Journal Radiology
    Excerpt

    PURPOSE: To retrospectively develop and evaluate computer-aided diagnosis (CAD) models that include both mammographic and sonographic descriptors. MATERIALS AND METHODS: Institutional review board approval was obtained for this HIPAA-compliant study. A waiver of informed consent was obtained. Mammographic and sonographic examinations were performed in 737 patients (age range, 17-87 years), which yielded 803 breast mass lesions (296 malignant, 507 benign). Radiologist-interpreted features from mammograms and sonograms were used as input features for linear discriminant analysis (LDA) and artificial neural network (ANN) models to differentiate benign from malignant lesions. An LDA with all the features was compared with an LDA with only stepwise-selected features. Classification performances were quantified by using receiver operating characteristic (ROC) analysis and were evaluated in a train, validate, and retest scheme. On the retest set, both LDAs were compared with radiologist assessment score of malignancy. RESULTS: Both the LDA and ANN achieved high classification performance with cross validation (area under the ROC curve [A(z)] = 0.92 +/- 0.01 [standard deviation] and (0.90)A(z) = 0.54 +/- 0.08 for LDA, A(z) = 0.92 +/- 0.01 and (0.90)A(z) = 0.55 +/- 0.08 for ANN). Results of both models generalized well to the retest set, with no significant performance differences between the validate and retest sets (P > .1). On the retest set, there were no significant performance differences between LDA with all features and LDA with only the stepwise-selected features (P > .3) and between either LDA and radiologist assessment score (P > .2). CONCLUSION: Results showed that combining mammographic and sonographic descriptors in a CAD model can result in high classification and generalization performance. On the retest set, LDA performance matched radiologist classification performance.

    Title Bayesian Networks of Bi-radstrade Mark Descriptors for Breast Lesion Classification.
    Date June 2007
    Journal Conference Proceedings : ... Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Conference
    Excerpt

    We investigated Bayesian network structure learning and probability estimation from mammographic feature data in order to classify breast lesions into different pathological categories. We compared the learned networks to naive Bayes classifiers, which are similar to the expert systems previously investigated for breast lesion classification. The learned network structures reflect the difference in the classification of biopsy outcome and the invasiveness of malignant lesions for breast masses and microcalcifications. The difference between masses and microcalcifications should be taken into consideration when interpreting systems for automatic pathological classification of breast lesions. The difference may also affect use of these systems for tasks such as estimating the sampling error of biopsy.

    Title Multiprojection Correlation Imaging for Improved Detection of Pulmonary Nodules.
    Date April 2007
    Journal Ajr. American Journal of Roentgenology
    Excerpt

    OBJECTIVE: The purpose of this study was the development and preliminary evaluation of multiprojection correlation imaging with 3D computer-aided detection (CAD) on chest radiographs for cost- and dose-effective improvement of early detection of pulmonary nodules. SUBJECTS AND METHODS: Digital chest radiographs of 10 configurations of a chest phantom and of seven human subjects were acquired in multiple angular projections with an acquisition time of 11 seconds (single breath-hold) and total exposure comparable with that of a posteroanterior chest radiograph. An initial 2D CAD algorithm with two difference-of-gaussians filters and multilevel thresholds was developed with an independent database of 44 single-view chest radiographs with confirmed lesions. This 2D CAD algorithm was used on each projection image to find likely suspect nodules. The CAD outputs were reconstructed in 3D, reinforcing signals associated with true nodules while simultaneously decreasing false-positive findings produced by overlapping anatomic features. The performance of correlation imaging was tested on two to 15 projection images. RESULTS: Optimum performance of correlation imaging was attained when nine projection images were used. Compared with conventional, single-view CAD, correlation imaging decreased as much as 79% the frequency of false-positive findings in phantom cases at a sensitivity level of 65%. The corresponding reduction in false-positive findings in the cases of human subjects was 78%. CONCLUSION: Although limited by a relatively simple CAD implementation and a small number of cases, the findings suggest that correlation imaging performs substantially better than single-view CAD and may greatly enhance identification of subtle solitary pulmonary nodules on chest radiographs.

    Title Evaluation of Information-theoretic Similarity Measures for Content-based Retrieval and Detection of Masses in Mammograms.
    Date February 2007
    Journal Medical Physics
    Excerpt

    The purpose of this study was to evaluate image similarity measures employed in an information-theoretic computer-assisted detection (IT-CAD) scheme. The scheme was developed for content-based retrieval and detection of masses in screening mammograms. The study is aimed toward an interactive clinical paradigm where physicians query the proposed IT-CAD scheme on mammographic locations that are either visually suspicious or indicated as suspicious by other cuing CAD systems. The IT-CAD scheme provides an evidence-based, second opinion for query mammographic locations using a knowledge database of mass and normal cases. In this study, eight entropy-based similarity measures were compared with respect to retrieval precision and detection accuracy using a database of 1820 mammographic regions of interest. The IT-CAD scheme was then validated on a separate database for false positive reduction of progressively more challenging visual cues generated by an existing, in-house mass detection system. The study showed that the image similarity measures fall into one of two categories; one category is better suited to the retrieval of semantically similar cases while the second is more effective with knowledge-based decisions regarding the presence of a true mass in the query location. In addition, the IT-CAD scheme yielded a substantial reduction in false-positive detections while maintaining high detection rate for malignant masses.

    Title Introduction to Neutron Stimulated Emission Computed Tomography.
    Date October 2006
    Journal Physics in Medicine and Biology
    Excerpt

    Neutron stimulated emission computed tomography (NSECT) is presented as a new technique for in vivo tomographic spectroscopic imaging. A full implementation of NSECT is intended to provide an elemental spectrum of the body or part of the body being interrogated at each voxel of a three-dimensional computed tomographic image. An external neutron beam illuminates the sample and some of these neutrons scatter inelastically, producing characteristic gamma emission from the scattering nuclei. These characteristic gamma rays are acquired by a gamma spectrometer and the emitting nucleus is identified by the emitted gamma energy. The neutron beam is scanned over the body in a geometry that allows for tomographic reconstruction. Tomographic images of each element in the spectrum can be reconstructed to represent the spatial distribution of elements within the sample. Here we offer proof of concept for the NSECT method, present the first single projection spectra acquired from multi-element phantoms, and discuss potential biomedical applications.

    Title Optimized Approach to Decision Fusion of Heterogeneous Data for Breast Cancer Diagnosis.
    Date October 2006
    Journal Medical Physics
    Excerpt

    As more diagnostic testing options become available to physicians, it becomes more difficult to combine various types of medical information together in order to optimize the overall diagnosis. To improve diagnostic performance, here we introduce an approach to optimize a decision-fusion technique to combine heterogeneous information, such as from different modalities, feature categories, or institutions. For classifier comparison we used two performance metrics: The receiving operator characteristic (ROC) area under the curve [area under the ROC curve (AUC)] and the normalized partial area under the curve (pAUC). This study used four classifiers: Linear discriminant analysis (LDA), artificial neural network (ANN), and two variants of our decision-fusion technique, AUC-optimized (DF-A) and pAUC-optimized (DF-P) decision fusion. We applied each of these classifiers with 100-fold cross-validation to two heterogeneous breast cancer data sets: One of mass lesion features and a much more challenging one of microcalcification lesion features. For the calcification data set, DF-A outperformed the other classifiers in terms of AUC (p < 0.02) and achieved AUC=0.85 +/- 0.01. The DF-P surpassed the other classifiers in terms of pAUC (p < 0.01) and reached pAUC=0.38 +/- 0.02. For the mass data set, DF-A outperformed both the ANN and the LDA (p < 0.04) and achieved AUC=0.94 +/- 0.01. Although for this data set there were no statistically significant differences among the classifiers' pAUC values (pAUC=0.57 +/- 0.07 to 0.67 +/- 0.05, p > 0.10), the DF-P did significantly improve specificity versus the LDA at both 98% and 100% sensitivity (p < 0.04). In conclusion, decision fusion directly optimized clinically significant performance measures, such as AUC and pAUC, and sometimes outperformed two well-known machine-learning techniques when applied to two different breast cancer data sets.

    Title Computer Aid for Decision to Biopsy Breast Masses on Mammography: Validation on New Cases.
    Date October 2005
    Journal Academic Radiology
    Excerpt

    RATIONALE AND OBJECTIVES: The purpose of this study was to validate the performance of a previously developed computer aid for breast mass classification for mammography on a new, independent database of cases not used for algorithm development. MATERIALS AND METHODS: A computer aid (classifier) based on the likelihood ratio (LRb) was previously developed on a database of 670 mass cases. The 670 cases (245 malignant) from one medical institution were described using 16 features from the American College of Radiology Breast Imaging-Reporting and Data System lexicon and patient history findings. A separate database of 151 (43 malignant) validation cases were collected that were previously unseen by the classifier. These new validation cases were evaluated by the classifier without retraining. Performance evaluation methods included Receiver Operating Characteristic (ROC), round-robin, and leave-one-out bootstrap sampling. RESULTS: The performance of the classifier on the training data yielded an average ROC area of 0.90 +/- 0.02 and partial ROC area (0.90AUC) of 0.60 +/- 0.06. The exact nonparametric performance on the validation set of 151 cases yielded a ROC area of 0.88 and 0.90AUC of 0.57. Using a 100% sensitivity cutoff threshold established on the training data (100% negative predictive value), the classifier correctly identified 100% of the malignant masses in the validation test set, while potentially obviating 26% of the biopsies performed on benign masses. CONCLUSION: The LRb classifier performed consistently on new data that was not used for classifier development. The LRb classifier shows promise as a potential aid in reducing the number of biopsies performed on benign masses.

    Title A Framework for Optimising the Radiographic Technique in Digital X-ray Imaging.
    Date September 2005
    Journal Radiation Protection Dosimetry
    Excerpt

    The transition to digital radiology has provided new opportunities for improved image quality, made possible by the superior detective quantum efficiency and post-processing capabilities of new imaging systems, and advanced imaging applications, made possible by rapid digital image acquisition. However, this transition has taken place largely without optimising the radiographic technique used to acquire the images. This paper proposes a framework for optimising the acquisition of digital X-ray images. The proposed approach is based on the signal and noise characteristics of the digital images and the applied exposure. Signal is defined, based on the clinical task involved in an imaging application, as the difference between the detector signal with and without a target present against a representative background. Noise is determined from the noise properties of uniformly acquired images of the background, taking into consideration the absorption properties of the detector. Incident exposure is estimated or otherwise measured free in air, and converted to dose. The main figure of merit (FOM) for optimisation is defined as the signal-difference-to-noise ratio (SdNR) squared per unit exposure or (more preferably) dose. This paper highlights three specific technique optimisation studies that used this approach to optimise the radiographic technique for digital chest and breast applications. In the first study, which was focused on chest radiography with a CsI flat-panel detector, a range of kV(p) (50-150) and filtration (Z = 13-82) were examined in terms of their associated FOM as well as soft tissue to bone contrast, a factor of importance in digital chest radiography. The results indicated that additive Cu filtration can improve image quality. A second study in digital mammography using a selenium direct flat-panel detector indicated improved SdNR per unit exposure with the use of a tungsten target and a rhodium filter than conventional molybdenum target/molybdenum filter techniques. Finally, a third study focusing on cone-beam computed tomography of the breast using a CsI flat-panel detector indicated that high Z filtration of a tungsten target X-ray beam can notably improve the signal and noise characteristics of the image. The general findings highlight the fact that the techniques that are conventionally assumed to be optimum may need to be revisited for digital radiography.

    Title Physical Characterization of a Prototype Selenium-based Full Field Digital Mammography Detector.
    Date June 2005
    Journal Medical Physics
    Excerpt

    The purpose of this study was to measure experimentally the physical performance of a prototype mammographic imager based on a direct detection, flat-panel array design employing an amorphous selenium converter with 70 microm pixels. The system was characterized for two different anode types, a molybdenum target with molybdenum filtration (Mo/Mo) and a tungsten target with rhodium filtration (W/Rh), at two different energies, 28 and 35 kVp, with approximately 2 mm added aluminum filtration. To measure the resolution, the presampled modulation transfer function (MTF) was measured using an edge method. The normalized noise power spectrum (NNPS) was measured by two-dimensional Fourier analysis of uniformly exposed mammograms. The detective quantum efficiencies (DQEs) were computed from the MTFs, the NNPSs, and theoretical ideal signal to noise ratios. The MTF was found to be close to its ideal limit and reached 0.2 at 11.8 mm(-1) and 0.1 at 14.1 mm(-1) for images acquired at an RQA-M2 technique (Mo/Mo anode, 28 kVp, 2 mm Al). Using a tungsten technique (MW2; W/Rh anode, 28 kVp, 2 mm Al), the MTF went to 0.2 at 11.2 mm(-1) and to 0.1 at 13.3 mm(-1). The DQE reached a maximum value of 54% at 1.35 mm(-1) for the RQA-M2 technique at 1.6 microC/kg and achieved a peak value of 64% at 1.75 mm(-1) for the tungsten technique (MW2) at 1.9 microC/kg. Nevertheless, the DQE showed strong exposure and frequency dependencies. The results indicated that the detector offered high MTFs and DQEs, but structured noise effects may require improved calibration before clinical implementation.

    Title Comparative Scatter and Dose Performance of Slot-scan and Full-field Digital Chest Radiography Systems.
    Date June 2005
    Journal Radiology
    Excerpt

    PURPOSE: To evaluate the scatter, dose, and effective detective quantum efficiency (DQE) performance of a slot-scan digital chest radiography system compared with that of a full-field digital radiography system. MATERIALS AND METHODS: Scatter fraction of a slot-scan system was measured for an anthropomorphic and a geometric phantom by using a posterior beam-stop technique at 117 and 140 kVp. Measurements were repeated with a full-field digital radiography system with and without a 13:1 antiscatter grid at 120 and 140 kVp. For both systems, the effective dose was measured on posteroanterior and lateral views for standard clinical techniques by using dosimeters embedded in a female phantom. The effective DQEs of the two systems were assessed by taking into account the scatter performance and the DQE of each system. The statistical significance of all the comparative differences was ascertained by means of t test analysis. RESULTS: The slot-scan system and the full-field system with grid yielded scatter fractions of 0.13-0.14 and 0.42-0.48 in the lungs and 0.30-0.43 and 0.69-0.78 in the mediastinum, respectively. The sum of the effective doses for posteroanterior and lateral views for the slot-scan system (0.057 mSv +/- 0.003 [+/- standard deviation]) was 34% lower than that for the full-field system (0.086 mSv +/- 0.001, P < .05) at their respective clinical peak voltages (140 and 120 kVp, respectively). The effective DQE of the slot-scan system was equivalent to that of the full-field system in the lung region but was 37% higher in the dense regions (P < .05). CONCLUSION: The slot-scan design leads to marked scatter reduction compared with the more conventional full-field geometries with a grid. The improved scatter performance of a slot-scan geometry can effectively compensate for low DQE and lead to improved image quality.

    Title Accuracy of Segmentation of a Commercial Computer-aided Detection System for Mammography.
    Date May 2005
    Journal Radiology
    Excerpt

    PURPOSE: To assess the accuracy of segmentation in a commercially available computer-aided detection (CAD) system. MATERIALS AND METHODS: Approval for this study was obtained from the authors' institutional review board. Informed consent was not required by the board for this review, as data were stripped of patient identifiers. Two thousand twenty mammograms from 507 women were analyzed with the hardware and software of a commercial CAD system. The accuracy of the segmentation process was determined semiquantitatively and categorized as near perfect if the skin line of the breast was accurately detected, acceptable if only subcutaneous fat was excluded, or unacceptable if any breast parenchyma was excluded from consideration. The accuracy of segmentation was compared for different breast densities and film sizes by using logistic regression (P < .05). RESULTS: Overall, segmentation was near perfect or acceptable in almost 96.8% of images. However, segmentation defects were significantly more common in mammograms with heterogeneously dense breast tissue (8% unacceptable) than in those with fatty replaced (0% unacceptable), scattered (1.2% unacceptable), or extremely dense (1.8% unacceptable) breast parenchyma (P < .05). For images with unacceptable segmentation, the average percentage of breast parenchyma excluded was almost 25% (range, 5%-100%), with no significant differences among breast densities. CONCLUSION: For one commercial CAD system, segmentation was usually near perfect or acceptable but was unacceptable more than five times more frequently for mammograms of breasts with heterogeneously dense parenchyma than for those with all other breast densities. On average, one-quarter of the breast parenchyma was excluded from CAD analysis for images with unacceptable segmentation.

    Title Fundamental Imaging Characteristics of a Slot-scan Digital Chest Radiographic System.
    Date February 2005
    Journal Medical Physics
    Excerpt

    Our purpose in this study was to evaluate the fundamental image quality characteristics of a new slot-scan digital chest radiography system (ThoraScan, Delft Imaging Systems/Nucletron, Veenendaal, The Netherlands). The linearity of the system was measured over a wide exposure range at 90, 117, and 140 kVp with added Al filtration. System uniformity and reproducibility were established with an analysis of images from repeated exposures. The modulation transfer function (MTF) was evaluated using an established edge method. The noise power spectrum (NPS) and the detective quantum efficiency (DQE) of the system were evaluated at the three kilo-voltages over a range of exposures. Scatter fraction (SF) measurements were made using a posterior beam stop method and a geometrical chest phantom. The system demonstrated excellent linearity, but some structured nonuniformities. The 0.1 MTF values occurred between 3.3-3.5 mm(-1). The DQE(0.15) and DQE(2.5) were 0.21 and 0.07 at 90 kVp, 0.18 and 0.05 at 117 kVp, and 0.16 and 0.03 at 140 kVp, respectively. The system exhibited remarkably lower SFs compared to conventional full-field systems with anti-scatter grid, measuring 0.13 in the lungs and 0.43 in the mediastinum. The findings indicated that the slot-scan design provides marked scatter reduction leading to high effective DQE (DQEeff) of the system and reduced patient dose required to achieve high image quality.

    Title Acute Fulminant Subacute Sclerosing Panencephalitis with Absent Measles and Pcr Studies in Cerebrospinal Fluid.
    Date December 2004
    Journal Pediatric Neurology
    Excerpt

    This report describes an atypical case of rapidly progressive subacute sclerosing panencephalitis presenting as transient visual agnosia and myoclonus in a 14-year-old male. There were no typical periodic complexes in serial electroencephalographic monitoring; cerebrospinal fluid measles antibody titer was negative. The diagnosis was made by molecular and histologic examination of open brain biopsy tissue.

    Title Computer-aided Detection in Screening Mammography: Variability in Cues.
    Date November 2004
    Journal Radiology
    Excerpt

    PURPOSE: To evaluate the variability of true-positive and false-positive cues by using a commercially available computer-aided detection (CAD) system for analysis of 50 malignancies in a screening population. MATERIALS AND METHODS: Fifty breast cancers detected at screening were analyzed by using a commercially available CAD system. Mean patient age was 62.2 years. Each set of mammograms (craniocaudal and mediolateral oblique views) was digitized and analyzed by the CAD system 10 times. One radiologist compared CAD output with the location of the malignancy at mammography and determined whether each lesion was marked accurately in one mammographic view, both views, or neither. Sensitivity and reproducibility of the CAD system were determined for both case- and image-based analysis. RESULTS: Overall sensitivity of the CAD system when at least one of the two mammographic views was marked correctly (case-base sensitivity) was 82.4%. Sensitivity when each mammographic view was considered separately (image-based sensitivity) was 61.1%. For case-based analysis, variability in true-positive CAD cues was demonstrated for 14 of 50 (28%) cases. For image-based analysis, inconsistency in CAD output was observed in 33 of 100 (33%) mammographic views that contained malignancies detected at screening. However, the CAD system consistently detected 40-43 of the 50 breast cancers in each of the 10 CAD runs. Variability for false-positive marks was significantly greater than that for true-positive marks. CONCLUSION: Inconsistency was demonstrated for CAD analysis of breast cancers detected at screening. However, the CAD system was reasonably consistent in the overall number of cancers identified from run to run. Greater variability of the CAD system was also demonstrated for false-positive marks, as compared with true-positive marks.

    Title A Hospital-sponsored Quality Improvement Study of Pain Management After Cesarean Delivery.
    Date July 2004
    Journal American Journal of Obstetrics and Gynecology
    Excerpt

    OBJECTIVE: We undertook this study to systematically assess prevailing pain management regimes used at our hospital in women after cesarean delivery. STUDY DESIGN: Between August 1999 and July 2000, all women delivered by cesarean section at Parkland Hospital were assigned to 1 of 4 different pain management strategies: (1). intramuscular (IM) meperidine, (2). patient-controlled analgesia (PCA) meperidine, (3). IM morphine sulfate, and (4). PCA morphine sulfate. A combination of methods were used to compare these different pain management strategies. A survey questionnaire, using Likert scale responses, was administered to evaluate maternal satisfaction with pain control. Visual Analog Scale (VAS) scores and information regarding breastfeeding and rooming-in were also collected. RESULTS: A total of 1256 women were allocated to the 4 analgesia study groups. The median meperidine dosages for the IM and PCA groups were 350 mg and 600 mg, respectively (P <or=.01). Conversely, the median IM morphine dose (65 mg) was significantly higher than that for the PCA group (60 mg). The percentage of women reporting moderate or worse pain (VAS scores 4 or more) was significantly lower in those women who received PCA meperidine compared with IM meperidine. Women who received morphine reported less severe pain compared with meperidine, regardless of route of administration. The patients' subjective report of satisfaction with pain management was not related to the method or drug used for pain control (P=.13). Fewer women assigned to morphine therapy stopped breastfeeding (P=.02) and more roomed-in with their infants (P <.01). CONCLUSION: Pain relief was superior with the morphine regimens used and was positively associated with breastfeeding and infant rooming-in.

    Title High Rate and Changing Molecular Epidemiology Pattern of Norovirus Infections in Sporadic Cases and Outbreaks of Gastroenteritis in Hong Kong.
    Date June 2004
    Journal Journal of Medical Virology
    Excerpt

    Noroviruses (Norwalk-like viruses (NLV)) are recognised as major causes of acute gastroenteritis worldwide. Numerous studies had been carried out on the molecular epidemiology of norovirus in outbreaks but relatively few on sporadic cases. In this study, the molecular epidemiology of noroviruses in sporadic and outbreak cases of acute gastroenteritis in Hong Kong was examined over a 12-month period from July 2001 to June 2002. Specimens from three groups of patients were used in this study. Nine hundred ninety-five specimens from patients enrolled in the Acute Diarrhoeal Diseases Surveillance Programme of the Department of Health, Hong Kong Government; 735 clinical specimens from hospital patients with acute gastroenteritis, and 122 specimens from 44 norovirus outbreaks. Ninety-two (9.2%) surveillance specimens were positive for norovirus RNA by reverse transcription-polymerase chain reaction (RT-PCR), compared to 123 (16.7%) clinical and 101 (82.8%) outbreak specimens. For the first 6 months of the study period, the predominant strain was the Bristol strain that belongs to genogroup II (GII). In the latter 6 months of the study, genogroup I (GI) and strains belonging to other clusters of GII were seen more commonly. The vast majority of strains belonging to the Bristol virus cluster were closely related to the 95/96-US subset that was associated with pandemic infection from 1995 onwards. This study clearly establishes the importance of norovirus as a cause of sporadic cases of acute gastroenteritis in all age groups in Hong Kong.

    Title Computer-aided Detection (cad) in Screening Mammography: Sensitivity of Commercial Cad Systems for Detecting Architectural Distortion.
    Date November 2003
    Journal Ajr. American Journal of Roentgenology
    Excerpt

    OBJECTIVE: Computer-aided detection (CAD) algorithms have successfully revealed breast masses and microcalcifications on screening mammography. The purpose of our study was to evaluate the sensitivity of commercially available CAD systems for revealing architectural distortion, the third most common appearance of breast cancer. MATERIALS AND METHODS: Two commercially available CAD systems were used to evaluate screening mammograms obtained in 43 patients with 45 mammographically detected regions of architectural distortion. For each CAD system, we determined the sensitivity for revealing architectural distortion on at least one image of the two-view mammographic examination (case sensitivity) and for each individual mammogram (image sensitivity). Surgical biopsy results were available for each case of architectural distortion. RESULTS: Architectural distortion was deemed present and actionable by a panel of expert breast imagers in 80 views of the 45 cases. One CAD system detected distortion in 22 of 45 cases of distortion (case sensitivity, 49%) and in 30 of 80 mammograms (image sensitivity, 38%); it displayed 0.7 false-positive marks per image. Another CAD system identified distortion in 15 of 45 cases (case sensitivity, 33%) and 17 of 80 mammograms (image sensitivity, 21%); it displayed 1.27 false-positive marks per image. Sensitivity for malignancy-caused distortion was similar to or lower than sensitivity for all causes of distortion. CONCLUSION: Fewer than one half of the cases of architectural distortion were detected by the two most widely available CAD systems used for interpretations of screening mammograms. Considerable improvement in the sensitivity of CAD systems is needed for detecting this type of lesion. Practicing breast imagers who use CAD systems should remain vigilant for architectural distortion.

    Title Ruptured Membranes at Term: Randomized, Double-blind Trial of Oral Misoprostol for Labor Induction.
    Date April 2003
    Journal Obstetrics and Gynecology
    Excerpt

    OBJECTIVE: To determine if oral misoprostol can replace oxytocin for labor stimulation in women with ruptured membranes at term and without evidence of labor. METHODS: Nulliparous women at 36 to 41 weeks with a singleton, cephalic-presenting fetus and ruptured membranes without evidence of labor were randomized to receive oral misoprostol (100 microg) or a placebo every 4 hours for a maximum of two doses. Intravenous oxytocin was initiated if active labor had not ensued within 8 hours of the initial study drug dose. RESULTS: Fifty-one women were randomized to oral misoprostol and 51 women to the placebo. Misoprostol reduced the use of oxytocin stimulation of labor from 90% to 37% (P <.001) and was associated with approximately a 7-hour shorter elapsed time in the labor unit. Uterine hyperactivity, defined as six or more contractions in 10 minutes without fetal heart rate decelerations, occurred in 25% of women randomized to misoprostol. However, uterine hyperactivity associated with fetal heart rate decelerations occurred in only three (6%) women, none of whom required emergency cesarean delivery. Route of delivery and infant outcomes were not related to misoprostol use. CONCLUSION: Oral misoprostol (100 microg) given in a maximum of two doses 4 hours apart significantly reduced the use of oxytocin in the management of women with ruptured membranes without labor at term.

    Title Parameter Optimization of a Computer-aided Diagnosis Scheme for the Segmentation of Microcalcification Clusters in Mammograms.
    Date November 2002
    Journal Medical Physics
    Excerpt

    Our purpose in this study is to develop a parameter optimization technique for the segmentation of suspicious microcalcification clusters in digitized mammograms. In previous work, a computer-aided diagnosis (CAD) scheme was developed that used local histogram analysis of overlapping subimages and a fuzzy rule-based classifier to segment individual microcalcifications, and clustering analysis for reducing the number of false positive clusters. The performance of this previous CAD scheme depended on a large number of parameters such as the intervals used to calculate fuzzy membership values and on the combination of membership values used by each decision rule. These parameters were optimized empirically based on the performance of the algorithm on the training set. In order to overcome the limitations of manual training and rule generation, the segmentation algorithm was modified in order to incorporate automatic parameter optimization. For the segmentation of individual microcalcifications, the new algorithm used a neural network with fuzzy-scaled inputs. The fuzzy-scaled inputs were created by processing the histogram features with a family of membership functions, the parameters of which were automatically extracted from the distribution of the feature values. The neural network was trained to classify feature vectors as either positive or negative. Individual microcalcifications were segmented from positive subimages. After clustering, another neural network was trained to eliminate false positive clusters. A database of 98 images provided training and testing sets to optimize the parameters and evaluate the CAD scheme, respectively. The performance of the algorithm was evaluated with a FROC analysis. At a sensitivity rate of 93.2%, there was an average of 0.8 false positive clusters per image. The results are very comparable with those taken using our previously published rule-based method. However, the new algorithm is more suited to generalize its performance on a larger population, depends on two monotonic outputs making its evaluation much easier and can be trained in an automatic way making practical its application on a large database.

    Title Outcome Analysis of Patients with Acute Pancreatitis by Using an Artificial Neural Network.
    Date September 2002
    Journal Academic Radiology
    Excerpt

    RATIONALE AND OBJECTIVES: The authors performed this study to evaluate the ability of an artificial neural network (ANN) that uses radiologic and laboratory data to predict the outcome in patients with acute pancreatitis. MATERIALS AND METHODS: An ANN was constructed with data from 92 patients with acute pancreatitis who underwent computed tomography (CT). Input nodes included clinical, laboratory, and CT data. The ANN was trained and tested by using a round-robin technique, and the performance of the ANN was compared with that of linear discriminant analysis and Ranson and Balthazar grading systems by using receiver operating characteristic analysis. The length of hospital stay was used as an outcome measure. RESULTS: Hospital stay ranged from 0 to 45 days, with a mean of 8.4 days. The hospital stay was shorter than the mean for 62 patients and longer than the mean for 30. The 23 input features were reduced by using stepwise linear discriminant analysis, and an ANN was developed with the six most statistically significant parameters (blood pressure, extent of inflammation, fluid aspiration, serum creatinine level, serum calcium level, and the presence of concurrent severe illness). With these features, the ANN successfully predicted whether the patient would exceed the mean length of stay (Az = 0.83 +/- 0.05). Although the Az performance of the ANN was statistically significantly better than that of the Ranson (Az = 0.68 +/- 0.06, P < .02) and Balthazar (Az = 0.62 +/- 0.06, P < .003) grades, it was not significantly better than that of linear discriminant analysis (Az = 0.82 +/- 0.05, P = .53). CONCLUSION: An ANN may be useful for predicting outcome in patients with acute pancreatitis.

    Title Computerized Classification of Suspicious Regions in Chest Radiographs Using Subregion Hotelling Observers.
    Date June 2002
    Journal Medical Physics
    Excerpt

    We propose to investigate the use of subregion Hotelling observers (SRHOs) in conjunction with perceptrons for the computerized classification of suspicious regions in chest radiographs for being nodules requiring follow up. Previously, 239 regions of interest (ROIs), each containing a suspicious lesion with proven classification, were collected. We chose to investigate the use of SRHOs as part of a multilayer classifier to determine the presence of a nodule. Each SRHO incorporates information about signal, background, and noise correlation for classification. For this study, 225 separate Hotelling observers were set up in a grid across each ROI. Each separate observer discriminates an 8 by 8 pixel area. A round robin sampling scheme was used to generate the 225 features, where each feature is the output of the individual observers. These features were then rank ordered by the magnitude of the weights of a perceptron. Once rank ordered, subsets of increasing number of features were selected to be used in another perceptron. This perceptron was trained to minimize mean squared error and the output was a continuous variable representing the likelihood of the region being a nodule. Performance was evaluated by receiver operating characteristic (ROC) analysis and reported as the area under the curve (Az). The classifier was optimized by adding additional features until the Az declined. The optimized subset of observers then were combined using a third perceptron. A subset of 80 features was selected which gave an Az of 0.972. Additionally, at 98.6% sensitivity, the classifier had a specificity of 71.3% and increased the positive predictive value from 60.7% to 84.1 %. Preliminary results suggest that using SRHOs in combination with perceptrons can provide a successful classification scheme for pulmonary nodules. This approach could be incorporated into a larger computer aided detection system for decreasing false positives.

    Title Differences Between Computer-aided Diagnosis of Breast Masses and That of Calcifications.
    Date June 2002
    Journal Radiology
    Excerpt

    To compare the performance of a computer-aided diagnosis (CAD) system for diagnosis of previously detected lesions, based on radiologist-extracted findings on masses and calcifications.

    Title Perceptron Error Surface Analysis: a Case Study in Breast Cancer Diagnosis.
    Date May 2002
    Journal Computers in Biology and Medicine
    Excerpt

    Perceptrons are typically trained to minimize mean square error (MSE). In computer-aided diagnosis (CAD), model performance is usually evaluated according to other more clinically relevant measures. The purpose of this study was to investigate the relationship between MSE and the area (A(z)) under the receiver operating characteristic (ROC) curve and the high-sensitivity partial ROC area ((0.90)A'(z)). A perceptron was used to predict lesion malignancy based on two mammographic findings and patient age. For each performance measure, the error surface in weight space was visualized. Comparison of the surfaces indicated that minimizing MSE tended to maximize A(z), but not (0.90)A'(z).

    Title Cross-institutional Evaluation of Bi-rads Predictive Model for Mammographic Diagnosis of Breast Cancer.
    Date February 2002
    Journal Ajr. American Journal of Roentgenology
    Excerpt

    OBJECTIVE: Given a predictive model for identifying very likely benign breast lesions on the basis of Breast Imaging Reporting and Data System (BI-RADS) mammographic findings, this study evaluated the model's ability to generalize to a patient data set from a different institution. MATERIALS AND METHODS: The artificial neural network model underwent three trials: it was optimized over 500 biopsy-proven lesions from Duke University Medical Center or "Duke," evaluated on 1,000 similar cases from the University of Pennsylvania Health System or "Penn," and reoptimized for Penn. RESULTS: Trial A's Duke-only model yielded 98% sensitivity, 36% specificity, area index (A(z)) of 0.86, and partial A(z) of 0.51. The cross-institutional trial B yielded 96% sensitivity, 28% specificity, A(z) of 0.79, and partial A(z) of 0.28. The decreases were significant for both A(z) (p = 0.017) and partial A(z) (p < 0.001). In trial C, the model reoptimized for the Penn data yielded 96% sensitivity, 35% specificity, A(z) of 0.83, and partial A(z) of 0.32. There were no significant differences compared with trial B for specificity (p = 0.44) or partial A(z) (p = 0.46), suggesting that the Penn data were inherently more difficult to characterize. CONCLUSION: The BI-RADS lexicon facilitated the cross-institutional test of a breast cancer prediction model. The model generalized reasonably well, but there were significant performance decreases. The cross-institutional performance was encouraging because it was not significantly different from that of a reoptimized model using the second data set at high sensitivities. This study indicates the need for further work to collect more data and to improve the robustness of the model.

    Title Effect of a Resident-created Study Guide on Examination Scores.
    Date January 2002
    Journal Obstetrics and Gynecology
    Excerpt

    OBJECTIVE: To evaluate the effect of a resident-created study guide on Council on Resident Education in Obstetrics and Gynecology (CREOG) In-Training and American Board of Obstetrics and Gynecology (ABOG) written examination scores. METHODS: In 1995, a group of residents at the University of Texas Southwestern Medical Center began creating an annual study guide based on the CREOG Test Item Summary Booklet. Individual, program, and national scores for 3 years before the intervention were compared with scores for 3 years after the intervention. A four-way analysis of variance was used to evaluate the effect of the intervention accounting for sex, Alpha Omega Alpha Medical Honor Society (AOA) status, and calendar year. A random effects model was also used to adjust for confounders. Categoric variables were compared using Mantel-Haenszel chi(2). Program failure rates for the ABOG written examination before and after the intervention were compared with relative risks. RESULTS: After introduction of the study guide, the annual difference between our program and the national percent correct increased significantly (2.1% versus 4.8%, P <.001), after adjustment for AOA status and calendar year. The improvement was distributed among resident levels 2-4 (all P <.02) and for non-AOA residents (P < or = .001). The relative risk of failure of the written ABOG examination before the study guide was 3.5 (95% confidence interval 0.77, 15.9). CONCLUSION: These findings demonstrate an important cooperative use of the Test Item Summary Booklet as an educational resource.

    Title A Neural Network Approach to Breast Cancer Diagnosis As a Constraint Satisfaction Problem.
    Date October 2001
    Journal Medical Physics
    Excerpt

    A constraint satisfaction neural network (CSNN) approach is proposed for breast cancer diagnosis using mammographic and patient history findings. Initially, the diagnostic decision to biopsy was formulated as a constraint satisfaction problem. Then, an associative memory type neural network was applied to solve the problem. The proposed network has a flexible, nonhierarchical architecture that allows it to operate not only as a predictive tool but also as an analysis tool for knowledge discovery of association rules. The CSNN was developed and evaluated using a database of 500 nonpalpable breast lesions with definitive histopathological diagnosis. The CSNN diagnostic performance was evaluated using receiver operating characteristic analysis (ROC). The results of the study showed that the CSNN ROC area index was 0.84+/-0.02. The CSNN predictive performance is competitive with that achieved by experienced radiologists and backpropagation artificial neural networks (BP-ANNs) presented before. Furthermore, the study illustrates how CSNN can be used as a knowledge discovery tool overcoming some of the well-known limitations of BP-ANNs.

    Title Case-based Reasoning Computer Algorithm That Uses Mammographic Findings for Breast Biopsy Decisions.
    Date November 2000
    Journal Ajr. American Journal of Roentgenology
    Excerpt

    We present case-based reasoning computer software developed from mammographic findings to provide support for the clinical decision to perform biopsy of the breast.

    Title Segmentation of Suspicious Clustered Microcalcifications in Mammograms.
    Date March 2000
    Journal Medical Physics
    Excerpt

    We have developed a multistage computer-aided diagnosis (CAD) scheme for the automated segmentation of suspicious microcalcification clusters in digital mammograms. The scheme consisted of three main processing steps. First, the breast region was segmented and its high-frequency content was enhanced using unsharp masking. In the second step, individual microcalcifications were segmented using local histogram analysis on overlapping subimages. For this step, eight histogram features were extracted for each subimage and were used as input to a fuzzy rule-based classifier that identified subimages containing microcalcifications and assigned the appropriate thresholds to segment any microcalcifications within them. The final step clustered the segmented microcalcifications and extracted the following features for each cluster: the number of microcalcifications, the average distance between microcalcifications, and the average number of times pixels in the cluster were segmented in the second step. Fuzzy logic rules incorporating the cluster features were designed to remove nonsuspicious clusters, defined as those with typically benign characteristics. A database of 98 images, with 48 images containing one or more microcalcification clusters, provided training and testing sets to optimize the parameters and evaluate the CAD scheme, respectively. The results showed a true positive rate of 93.2% and an average of 0.73 false positive clusters per image. A comparison of our results with other reported segmentation results on the same database showed comparable sensitivity and at the same time an improved false positive rate. The performance of the CAD scheme is encouraging for its use as an automatic tool for efficient and accurate diagnosis of breast cancer.

    Title A Neural Network to Predict Symptomatic Lung Injury.
    Date October 1999
    Journal Physics in Medicine and Biology
    Excerpt

    A nonlinear neural network that simultaneously uses pre-radiotherapy (RT) biological and physical data was developed to predict symptomatic lung injury. The input data were pre-RT pulmonary function, three-dimensional treatment plan doses and demographics. The output was a single value between 0 (asymptomatic) and 1 (symptomatic) to predict the likelihood that a particular patient would become symptomatic. The network was trained on data from 97 patients for 400 iterations with the goal to minimize the mean-squared error. Statistical analysis was performed on the resulting network to determine the model's accuracy. Results from the neural network were compared with those given by traditional linear discriminate analysis and the dose-volume histogram reduction (DVHR) scheme of Kutcher. Receiver-operator characteristic (ROC) analysis was performed on the resulting network which had Az = 0.833 +/- 0.04. (Az is the area under the ROC curve.) Linear discriminate multivariate analysis yielded an Az = 0.813 +/- 0.06. The DVHR method had Az = 0.521 +/- 0.08. The network was also used to rank the significance of the input variables. Future studies will be conducted to improve network accuracy and to include functional imaging data.

    Title An Evaluation of Susceptibility Testing Methods for Ampicillin-sulbactam Using a Panel of Beta-lactamase-producing Bacteria.
    Date August 1999
    Journal Apmis : Acta Pathologica, Microbiologica, Et Immunologica Scandinavica
    Excerpt

    Bacteria possessing TEM-1-like beta-lactamases are generally regarded as susceptible to ampicillin-sulbactam (SAM), while those harboring OXA-1 enzymes are considered resistant. The current study was undertaken to compare susceptibility testing using various combinations of ampicillin and sulbactam to improve clinical correlation. Members of the Enterobacteriaceae family harboring TEM-1, SHV-1 or OXA-1-like beta-lactamases were tested using the agar dilution method. A substantial proportion of strains harboring OXA-1-like beta-lactamases showed false susceptibility to SAM at the 1:1 ratio or fixed sulbactam concentration of 8 microg/ml. At a fixed sulbactam concentration of 4 microg/ml, the activity of ampicillin-sulbactam appeared to be reduced, with large numbers of TEM-1 producers becoming frankly resistant. Results obtained with the 2:1 ratio exhibited the closest correlation with that obtained by the currently recommended disk diffusion test. However, very major errors were still found between the disk diffusion test and agar dilution test, suggesting the necessity for consideration of a change in criteria for interpretation of disk diffusion test results. In conclusion, SAM susceptibility testing by agar dilution using other than a 2:1 ratio is not recommended and results should be interpreted with caution.

    Title Difference in Seroprevalence of Herpes Simplex Virus Type 2 Infection Among Antenatal Women in Hong Kong and Southern China.
    Date August 1999
    Journal Sexually Transmitted Infections
    Title Effect of Patient History Data on the Prediction of Breast Cancer from Mammographic Findings with Artificial Neural Networks.
    Date March 1999
    Journal Academic Radiology
    Excerpt

    RATIONALE AND OBJECTIVES: The authors evaluated the contribution of medical history data to the prediction of breast cancer with artificial neural network (ANN) models based on mammographic findings. MATERIALS AND METHODS: Three ANNs were developed: The first used 10 Breast Imaging Reporting and Data System (BI-RADS) variables; the second, the BI-RADS variables plus patient age; the third, the BI-RADS variables, patient age, and seven other history variables, for a total of 18 inputs. Performance of the ANNs and the original radiologist's impression were evaluated with five metrics: receiver operating characteristic area index (Az); specificity at given sensitivities of 100%, 98%, and 95%; and positive predictive value. RESULTS: All three ANNs consistently outperformed the radiologist's impression over all five performance metrics. The patient-age variable was particularly valuable. Adding the age variable to the basic ANN model, which used only the BI-RADS findings, significantly improved Az (P = .028). In fact, replacing all history data with just the age variable resulted in virtually no changes for Az or specificity at 98% sensitivity (P = .324 and P = .410, respectively). CONCLUSION: Patient age was an important variable for the prediction of breast cancer from mammographic findings with the ANNs. For this data set, all history data could be replaced with age alone.

    Title Correlation of in Vitro Susceptibility Testing Results for Amoxicillin-clavulanate and Ampicillin-sulbactam Using a Panel of Beta-lactamase-producing Enterobacteriaceae.
    Date November 1998
    Journal Apmis : Acta Pathologica, Microbiologica, Et Immunologica Scandinavica
    Excerpt

    Correlation between in vitro susceptibility results for amoxicillin-clavulanate (AMC) and ampicillin-sulbactam (SAM) was studied using 136 clinical and control strains of Enterobacteriaceae harboring TEM-1, SHV-1 or OXA-1-like beta-lactamases. Determination of minimal inhibitory concentration of antibiotics was performed by agar dilution. The beta-lactamases were initially characterized using isoelectric focusing. Further identification was done by DNA hybridization with or without prior PCR amplification. All strains sensitive to SAM were found to be sensitive also to AMC. In contrast, among those susceptible to AMC, only 50% were sensitive to SAM while 36% gave intermediate results and 14% were resistant. Major differences were found solely among SHV-producers while minor differences occurred mostly among TEM-producers. This phenomenon is probably related to the differential activities of clavulanate and sulbactam against various beta-lactamases. In conclusion, testing of Enterobacteriaceae isolates for susceptibility to AMC and SAM should be performed and reported individually to avoid erroneous designation of susceptibility.

    Title Predictive Model for the Diagnosis of Intraabdominal Abscess.
    Date September 1998
    Journal Academic Radiology
    Excerpt

    RATIONALE AND OBJECTIVES: The authors investigated the use of an artificial neural network (ANN) to aid in the diagnosis of intraabdominal abscess. MATERIALS AND METHODS: An ANN was constructed based on data from 140 patients who underwent abdominal and pelvic computed tomography (CT) between January and December 1995. Input nodes included data from clinical history, physical examination, laboratory investigation, and radiographic study. The ANN was trained and tested on data from all 140 cases by using a round-robin method and was compared with linear discriminate analysis. A receiver operating characteristic curve was generated to evaluate both predictive models. RESULTS: CT examinations in 50 cases were positive for abscess. This finding was confirmed by means of laboratory culture of aspirations from CT-guided percutaneous drainage in 38 patients, ultrasound-guided percutaneous drainage in five patients, surgery in five patients, and characteristic appearance on CT scans without aspiration in two patients. CT scans in 90 cases were negative for abscess. The sensitivity and specificity of the ANN in predicting the presence of intraabdominal abscess were 90% and 51%, respectively. Receiver operating characteristic analysis showed no statistically significant difference in performance between the two predictive models. CONCLUSION: The ANN is a useful tool for determining whether an intraabdominal abscess is present. It can be used to set priorities for CT examinations in order to expedite treatment in patients believed to be more likely to have an abscess.

    Title Computer-aided Diagnosis of Breast Cancer: Artificial Neural Network Approach for Optimized Merging of Mammographic Features.
    Date February 1998
    Journal Academic Radiology
    Excerpt

    RATIONALE AND OBJECTIVES: An artificial neural network (ANN) approach was developed for the computer-aided diagnosis of mammography using an optimally minimized number of input features. METHODS: A backpropagation ANN merged nine input features (age plus eight radiographic findings extracted by radiologists) to predict biopsy outcome as its output. The features were ranked, and more important ones were selected to produce an optimal subset of features. RESULTS: Given all nine features, the ANN performed with a receiver operator characteristic area under the curve (Az) of .95 +/- .01. Given only the four most important features, the ANN performed with an Az of .96 +/- .01. Although not significantly better than the ANN with all nine features, the ANN with the four optimized features was significantly better than expert radiologists' Az of .90 +/- .02 (p = .01). This four-feature ANN had a 95% sensitivity and an 81% specificity. For cases with calcifications, the radiologists' performance dropped to an Az of .85 +/- .04, whereas a specialized three-feature ANN performed significantly better with an Az of .95 +/- .02 (p = .02). CONCLUSION: Given only four input features, the ANN predicted biopsy outcome significantly better than did expert radiologists, who also had access to other radiographic and nonradiographic data. The reduced number of features would substantially decrease data entry efforts and potentially improve the ANN's general applicability.

    Title Herpes Simplex Virus Type 2 Infection in a 5-year-old Boy Presenting with Recurrent Chest Wall Vesicles and a Possible History of Herpes Encephalitis.
    Date November 1997
    Journal The British Journal of Dermatology
    Excerpt

    A 5-year-old hyperkinetic but otherwise healthy child presented with recurrent irritable vesicles and erosions of the anterior chest wall; they have been apparent since the age of 15 months. Wound swab cultures yielded herpes simplex virus type-2 (HSV-2) and Western blot serology showed past exposure to both HSV-1 and HSV-2. Skin biopsy results further supported a herpes virus infection. Magnetic resonance imaging of the brain showed right temporal lobe atrophy. An evaluation showed no evidence of sexual abuse in the patient but a Western blot assay of the mother's serum for HSV-2 was positive, while the father's was negative. In view of the diagnosis of HSV-2 infection in such a young patient, the possible routes of transmission and the time of acquisition of infection were explored. We believe the most likely route of infection in this child was postnatal, through intimate contact with the mother.

    Title Vancomycin and Amikacin in Cell Cultures for Virus Isolation.
    Date June 1997
    Journal Pathology
    Excerpt

    Contamination of cell cultures for virus isolation has been increasingly encountered. By reviewing and changing the antimicrobials incorporated in cell culture media, we aim to control this problem. Contaminated cell culture fluids were inoculated for bacterial and fungal isolation, identification and antibacterial susceptibility testing. Based on the above results, vancomycin and amikacin were chosen to replace the penicillin and gentamicin used conventionally. Analysis was carried out on various characteristics of cell culture with respect to antimicrobial change. All contaminating Gram-positive bacteria were susceptible to vancomycin while about 80% of the Gram-negative bacteria were sensitive to amikacin. The new antimicrobial combination was not toxic to cell cultures and both antimicrobials were found to remain stable in media for over six months. The virus isolation rate was maintained after antimicrobial change while the contamination rate was reduced from nearly 10% to 1.5%. We thus conclude that vancomycin and amikacin can well replace the conventional penicillin and gentamicin to be incorporated into maintenance and transport media to control the emerging problem of viral culture contamination.

    Title Predicting Breast Cancer Invasion with Artificial Neural Networks on the Basis of Mammographic Features.
    Date April 1997
    Journal Radiology
    Excerpt

    PURPOSE: To evaluate whether an artificial neural network (ANN) can predict breast cancer invasion on the basis of readily available medical findings (ie, mammographic findings classified according to the American College of Radiology Breast Imaging Reporting and Data System and patient age). MATERIALS AND METHODS: In 254 adult patients, 266 lesions that had been sampled at biopsy were randomly selected for the study. There were 96 malignant and 170 benign lesions. On the basis of nine mammographic findings and patient age, a three-layer backpropagation network was developed to predict whether the malignant lesions were in situ or invasive. RESULTS: The ANN predicted invasion among malignant lesions with an area under the receiver operating characteristic curve (Az) of .91 +/- .03. It correctly identified all 28 in situ cancers (specificity, 100%) and 48 of 68 invasive cancers (sensitivity, 71%). CONCLUSION: The ANN used mammographic features and patient age to accurately classify invasion among breast cancers, information that was previously available only by means of biopsy. This knowledge may assist in surgical planning and may help reduce the cost and morbidity of unnecessary biopsy.

    Title Diffuse Nodular Lung Disease on Chest Radiographs: a Pilot Study of Characterization by Fractal Dimension.
    Date December 1996
    Journal Ajr. American Journal of Roentgenology
    Excerpt

    OBJECTIVE: We present a computer-aided diagnostic technique for identifying nodular interstitial lung disease on chest radiographs. The fractal dimension was used as a numerical measure of image texture on digital chest radiographs to distinguish patients with normal lung from those with a diffuse nodular interstitial abnormality. MATERIALS AND METHODS: Twenty digitized chest radiographs were classified as normal (n = 10) or as containing diffuse nodular abnormality (n = 10) on the basis of readings assigned according to the classification of the International Labour Organization. Regions of interest (ROIs) measuring 1.28 cm2 were selected from the intercostal spaces of these radiographs. The fractal dimension of these ROIs was estimated by power spectrum analysis. The cases were not subtle. RESULTS: The fractal dimension provided statistically significant discrimination between normal parenchyma and nodular interstitial lung disease. The area under the receiver operating characteristic curve was 0.90 (+/- 0.02). One operating point provides sensitivity of 88% with a specificity of 80%. CONCLUSION: The fractal dimension can provide a measure of lung parenchymal texture and shows promise as an element of computer-aided diagnosis, characterization, and follow-up of interstitial lung disease.

    Title Immunochemical Quantitation of Lipoprotein Lipase.
    Date November 1996
    Journal Methods in Enzymology
    Title Structure-function Relationship of Lipoprotein Lipase-mediated Enhancement of Very Low Density Lipoprotein Binding and Catabolism by the Low Density Lipoprotein Receptor. Functional Importance of a Properly Folded Surface Loop Covering the Catalytic Center.
    Date October 1996
    Journal The Journal of Biological Chemistry
    Excerpt

    We examined the structure-function relationship of human lipoprotein lipase (hLPL) in its ability to enhance the binding and catabolism of very low density lipoproteins (VLDL) in COS cells. Untransfected COS cells did not bind to or catabolize normal VLDL. Expression of wild-type hLPL by transient transfection enhanced binding, uptake, and degradation of the VLDL (a property of LPL that we call bridge function). Heparin pretreatment and a monoclonal antibody ID7 that blocks LDL receptor-binding domain of apoE both inhibited binding, and apoE2/E2 VLDL from a Type III hyperlipidemic subject did not bind. However, LDL did not reduce 125I-VLDL binding to the hLPL-expressing cells, whereas rabbit beta-VLDL was an effective competitor. By contrast, LDL reduced uptake and degradation of 125I-VLDL to the same extent as excess unlabeled VLDL or beta-VLDL. These data suggest that binding occurs by direct interaction of VLDL with LPL but the subsequent catabolism of the VLDL is mediated by the LDL receptor. Mutant hLPLs that were catalytically inactive, S132A, S132D, as well as the partially active mutant, S251T, and S172G, gave normal enhancement of VLDL binding and catabolism, whereas the partially active mutant S172D had markedly impaired capacity for the process; thus, there is no correlation between bridge function and lipolytic activity. A naturally occurring genetic variant hLPL, S447-->Ter, has normal bridge function. The catalytic center of LPL is covered by a 21-amino acid loop that must be repositioned before a lipid substrate can gain access to the active site for catalysis. We studied three hLPL loop mutants (LPL-cH, an enzymatically active mutant with the loop replaced by a hepatic lipase loop; LPL-cP, an enzymatically inactive mutant with the loop replaced by a pancreatic lipase loop; and C216S/C239S, an enzymatically inactive mutant with the pair of Cys residues delimiting the loop substituted by Ser residues) and a control double Cys mutant, C418S/C438S. Two of the loop mutants (LPL-cH and LPL-cP) and the control double Cys mutant C418S/C438S gave normal enhancement of VLDL binding and catabolism, whereas the third loop mutant, C216S/C239S, was completely inactive. We conclude that although catalytic activity and the actual primary sequence of the loop of LPL are relatively unimportant (wild-type LPL loop and pancreatic lipase loops have little sequence similarity), the intact folding of the loop, flanked by disulfide bonds, must be maintained for LPL to express its bridge function.

    Title Artificial Neural Network: Improving the Quality of Breast Biopsy Recommendations.
    Date February 1996
    Journal Radiology
    Excerpt

    PURPOSE: To evaluate the performance and inter- and intraobserver variability of an artificial neural network (ANN) for predicting breast biopsy outcome. MATERIALS AND METHODS: Five radiologists described 60 mammographically detected lesions with the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) nomenclature. A previously programmed ANN used the BI-RADS descriptors and patient histories to predict biopsy results. ANN predictive performance was compared with the clinical decision to perform biopsy. Inter- and intraobserver variability of radiologists' interpretations and ANN predictions were evaluated with Cohen kappa analysis. RESULTS: The ANN maintained 100% sensitivity (23 of 23 cancers) while improving the positive predictive value of biopsy results from 38% (23 of 60 lesions) to between 58% (23 of 40 lesions) and 66% (23 of 35 lesions; P < .001). Interobserver variability for interpretation of the lesions was significantly reduced by the ANN (P < .001); there was no statistically significant effect on nearly perfect intraobserver reproducibility. CONCLUSION: Use of an ANN with radiologists' descriptions of abnormal findings may improve interpretation of mammographic abnormalities.

    Title Breast Cancer: Prediction with Artificial Neural Network Based on Bi-rads Standardized Lexicon.
    Date September 1995
    Journal Radiology
    Excerpt

    PURPOSE: To determine if an artificial neural network (ANN) to categorize benign and malignant breast lesions can be standardized for use by all radiologists. MATERIALS AND METHODS: An ANN was constructed based on the standardized lexicon of the Breast Imaging Recording and Data System (BI-RADS) of the American College of Radiology. Eighteen inputs to the network included 10 BI-RADS lesion descriptors and eight input values from the patient's medical history. The network was trained and tested on 206 cases (133 benign, 73 malignant cases). Receiver operating characteristic curves for the network and radiologists were compared. RESULTS: At a specified output threshold, the ANN would have improved the positive predictive value (PPV) of biopsy from 35% to 61% with a relative sensitivity of 100%. At a fixed sensitivity of 95%, the specificity of the ANN (62%) was significantly greater than the specificity of radiologists (30%) (P < .01). CONCLUSION: The BI-RADS lexicon provides a standardized language between mammographers and an ANN that can improve the PPV of breast biopsy.

    Title Bayesian Restoration of Chest Radiographs. Scatter Compensation with Improved Signal-to-noise Ratio.
    Date March 1995
    Journal Investigative Radiology
    Excerpt

    OBJECTIVES. The authors introduce a Bayesian algorithm for digital chest radiography that increases the signal-to-noise ratio, and thus detectability, for low-contrast objects. METHOD. The improved images are formed as a maximum a posteriori probability estimation of a scatter-reduced (contrast-enhanced) image with decreased noise. Noise is constrained by including prior knowledge of image smoothness. Variations between neighboring pixels are penalized for small variations (to suppress Poisson noise), but not for larger variations (to avoid affecting anatomical structure). The technique was optimized to reduce residual scatter in digital radiographs of an anatomical chest phantom. RESULTS. The contrast in the lung was improved by a factor of two, whereas signal-to-noise ratio was improved by a factor of 1.8. Image resolution was unaffected for objects with a contrast greater than 2%. CONCLUSION. This statistical estimation technique shows promise for improving object detectability in radiographs by simultaneously increasing contrast, while constraining noise.

    Title Lipoprotein Lipase: Role of Intramolecular Disulfide Bonds in Enzyme Catalysis.
    Date February 1995
    Journal Biochemical and Biophysical Research Communications
    Excerpt

    Lipoprotein lipase (LPL) catalyzes the hydrolysis of the triacylglycerol component of triacylglycerol-rich lipoproteins. There are 4 cysteine pairs that are completely conserved among LPLs of all species known. We examined the functional importance of each of the cysteine pairs in enzyme catalysis by examining LPLs produced in Cos cells by transfection. Immunoreactive LPL was produced by vectors encoding the wildtype LPL and each of the 4 cysteine-pair mutant LPLs. Enzyme activity was detectable in the wildtype enzyme, but not in 3 of the 4 Cys-->Ser mutant enzymes (C216S/C239S, C264S/C275S, and C278S/C283S). Interestingly, LPL activity was also present in the mutant (C418S/C438S), which affects the C-terminal cysteine pair, with a specific activity approximately 50% higher than that of wildtype. There is evidence that LPL contains two distinct domains consisting of the N-terminal three-quarters of the sequence connected by a flexible region to the C-terminal domain comprising the rest of the molecule. The conservation of catalytic function despite the disruption of the only disulfide bridge in the C-terminal domain of LPL indicates that the two domains can function independently of each other in enzyme catalysis.

    Title Prediction of Breast Cancer Malignancy Using an Artificial Neural Network.
    Date December 1994
    Journal Cancer
    Excerpt

    BACKGROUND. An artificial neural network (ANN) was developed to predict breast cancer from mammographic findings. This network was evaluated in a retrospective study. METHODS. For a set of patients who were scheduled for biopsy, radiologists interpreted the mammograms and provided data on eight mammographic findings as part of the standard mammographic workup. These findings were encoded as features for an ANN. Results of biopsies were taken as truth in the diagnosis of malignancy. The ANN was trained and evaluated using a jackknife sampling on a set of 260 patient records. Performance of the network was evaluated in terms of sensitivity and specificity over a range of decision thresholds and was expressed as a receiver operating characteristic curve. RESULTS. The ANN performed more accurately than the radiologists (P < 0.08) with a relative sensitivity of 1.0 and specificity of 0.59. CONCLUSIONS. An ANN can be trained to predict malignancy from mammographic findings with a high degree of accuracy.

    Title Scatter Compensation in Digital Chest Radiography Using the Posterior Beam Stop Technique.
    Date July 1994
    Journal Medical Physics
    Excerpt

    A new scatter compensation technique for computed radiography based on posterior beam stop (PBS) sampled scatter measurements and the bicubic spline interpolation technique was proposed. Using only a single exposure, both the clinical image and an array of scatter measurements, which were interpolated into a smooth scatter-only image, were simultaneously acquired. The scatter was subtracted from the clinical image to generate the primary-only image. To gauge the accuracy of scatter estimation, both quantitative and interpolation errors were evaluated. The PBS measurements were compared against the standard beam stop method at 16 locations in an anatomical phantom, resulting in quantitative errors of 2.7% relative to the scatter or 6.8% relative to the primary. Also measured were the interpolation error over 64 interpolation sample locations and 64 midpoint sample locations in the anatomical phantom. The combined interpolation error was 1.9% relative to the scatter or 8.0% relative to the primary. At the interpolation sample locations, the errors were identical between the phantom radiograph and digital portable chest radiographs from five patients. By summing the quantitative and interpolation errors in quadrature, the overall error of the PBS SISTER (scatter interpolation-subtraction technique for radiography) method was 3.3% relative to the scatter or 10% relative to the primary, which was adequate for dual-energy imaging purposes (less than 10% error relative to the scatter or 20% relative to the primary). The change of image contrast, noise, and signal-to-noise ratio (SNR) at six locations in the anatomical phantom were quantitatively analyzed. Contrast and noise were equally enhanced in all anatomical regions, resulting in approximately the same SNR before and after compensation.(ABSTRACT TRUNCATED AT 250 WORDS)

    Title An Artificial Neural Network for Estimating Scatter Exposures in Portable Chest Radiography.
    Date November 1993
    Journal Medical Physics
    Excerpt

    An adaptive linear element (Adaline) was developed to estimate the two-dimensional scatter exposure distribution in digital portable chest radiographs (DPCXR). DPCXRs and quantitative scatter exposure measurements at 64 locations throughout the chest were acquired for ten radiographically normal patients. The Adaline is an artificial neural network which has only a single node and linear thresholding. The Adaline was trained using DPCXR-scatter measurement pairs from five patients. The spatially invariant network would take a portion of the image as its input and estimate the scatter content as output. The trained network was applied to the other five images, and errors were evaluated between estimated and measured scatter values. Performance was compared against a convolution scatter estimation algorithm. The network was evaluated as a function of network size, initial values, and duration of training. Network performance was evaluated qualitatively by the correlation of network weights to physical models, and quantitatively by training and evaluation errors. Using DPCXRs as input, the network learned to describe known scatter exposures accurately (7% error) and estimate scatter in new images (< 8% error) slightly better than convolution methods. Regardless of size and initial shape, all networks adapted into radial exponentials with magnitude of 0.75, perhaps implying an ideal point spread function and average scatter fraction, respectively. To implement scatter compensation, the two-dimensional scatter distribution estimated by the neural network is subtracted from the original DPCXR.

    Title Observer Evaluation of Scatter Subtraction for Digital Portable Chest Radiographs.
    Date October 1993
    Journal Investigative Radiology
    Excerpt

    RATIONALE AND OBJECTIVES. The authors compared standard digital portable chest radiographs (DPCXR) to scatter-subtracted DPCXR. METHODS. Thirty DPCXR were obtained using a photostimulable phosphor digital imaging system and a posterior beam stop (PBS) technique that allowed measurement of the scatter component of the DPCXR. The scatter component was subtracted from the clinical image to form a scatter-subtracted image. Six observers recorded preference for the standard image or scatter-subtracted image for identifying five radiographic landmarks and for image quality. RESULTS. A statistically significant preference was demonstrated for the scatter-subtracted images and for viewing the tracheo-bronchial tree, right paratracheal stripe, vertebral column, and support apparatus position. For unprocessed images, there was a statistically significant preference for viewing the pulmonary vasculature. No statistically significant preference was demonstrated for overall image quality. CONCLUSIONS. These results suggest that PBS scatter subtraction holds promise for improving visualization of structures in high-scatter regions of chest radiographs.

    Title Measurement of Scatter Fractions in Erect Posteroanterior and Lateral Chest Radiography.
    Date July 1993
    Journal Radiology
    Excerpt

    Scatter fractions (SFs) measured in patients undergoing erect posteroanterior (PA) and lateral chest radiography with a 12:1 antiscatter grid are reported. Modifications to the posterior beam-stop (PBS) technique allowed measurement of scatter in these patients, without altering the diagnostic image and without additional radiation exposure. The SF measurements are reported by anatomic location on 42 clinical chest images. Average SF values ranged from 0.27 to 0.90 on lateral radiographs and from 0.27 to 0.68 on PA radiographs. Scatter measurements with the 12:1 grid were found to be greater than estimates from previous PA chest phantom experiments. To the authors' knowledge, they were the first to measure radiation scatter with the PBS technique in patients undergoing PA and lateral chest radiography with the antiscatter grid.

    Title Scatter Compensation for Digital Chest Radiography Using Maximum Likelihood Expectation Maximization.
    Date June 1993
    Journal Investigative Radiology
    Excerpt

    RATIONALE AND OBJECTIVES. An iterative maximum likelihood expectation maximization algorithm (MLEM) has been developed for scatter compensation in chest radiography. METHODS. The MLEM technique produces a scatter-reduced image which maximizes the probability of observing the measured image. We examined the scatter content and the low-contrast signal-to-noise ratio (SNR) in digital radiographs of anatomical phantoms before and after compensation. RESULTS. MLEM converged to an accurate (6.4% RMS residual scatter error) estimate within 12 iterations. Both contrast and noise were increased in the processed images as iteration progressed. In the lung, contrast was increased 108% and SNR was improved by 10%. In the retrocardiac region, contrast was increased 180% while SNR decreased by 6%. CONCLUSIONS. This is the first report of a post-acquisition scatter compensation technique which can increase SNR. These results suggest that statistical estimation techniques can enhance image quality and quantitative accuracy for digital chest radiography.

    Title Posterior Beam-stop Method for Scatter Fraction Measurement in Digital Radiography.
    Date July 1992
    Journal Investigative Radiology
    Excerpt

    The authors presented a new posterior beam-stop (PBS) technique for measuring the ratio of scattered to total-detected photon flux (scatter fraction) in a radiographic examination while preserving the diagnostic quality of the image. The scatter measurement was made using a standard imaging geometry with both beam stops and an additional x-ray detector placed behind the standard imaging detector. This PBS geometry differs from the standard beam-stop (SBS) technique for scatter measurement. With SBS, a beam-stop shadow appears on the image. To evaluate the PBS technique, scatter fraction measurements were performed on an anatomic phantom using both the PBS and SBS techniques. When compared with the standard technique, PBS provided accurate estimation of scatter fractions. Since the measurement can be performed without degrading a standard clinical radiographic examination, the PBS technique allows simultaneous acquisition of scatter measurements from human patients in combination with a standard radiographic examination.

    Title Measurement of Scatter Fractions in Clinical Bedside Radiography.
    Date June 1992
    Journal Radiology
    Excerpt

    The authors present measurements of scatter fraction (SF), the ratio of scattered to total imaged photons, from clinical bedside radiographs of 102 patients. These measurements were obtained by using a new posterior beam-stop technique that does not alter the diagnostic image but that simultaneously provides SF measurements at 224 locations in the image. The SF values in the lung were found to be consistent with previous measurements, while the SF values in the mediastinal and retrocardiac areas were larger than previously reported. SFs in diseased lung were significantly larger than SFs in normal lung. The range of SF values was large for all anatomic locations. For applications in which accurate scatter estimation is required, this wide range of values suggests that SFs should be measured in each individual image.

    Title Quantitative Scatter Measurement in Digital Radiography Using a Photostimulable Phosphor Imaging System.
    Date September 1991
    Journal Medical Physics
    Excerpt

    X-ray scatter fractions measured with two detectors are compared: a photostimulable phosphor system (PSP) and a conventional film-screen technique. For both detection methods, a beam-stop technique was used to estimate the scatter fraction in polystyrene phantoms. These scatter fraction measurements are compared to previously reported film-based measurements. Scatter fractions obtained with the PSP were in good agreement both with measurements using film as well as with most previously reported measurements. For the PSP measurements, repeatability was better than 1%. It was found that the PSP provides a precise x-ray detector for quantitative scatter measurement in digital radiography.

    Title Scatter Fractions in Amber Imaging.
    Date January 1991
    Journal Radiology
    Excerpt

    Images of two phantoms were obtained with use of an advanced multiple-beam equalization radiography system, and scatter fractions were estimated with use of a photostimulable phosphor imaging system. Scatter fractions in the equalized images were lower in the mediastinum-equivalent areas and higher in the lung-equivalent areas, relative to images that were conventionally acquired with use of an antiscatter grid. The differences are attributed to a reduction in incident exposure in the lungs and the presence of cross-scatter between lung and mediastinal regions.

    Title Unsuspected Extracolonic Findings at Screening Ct Colonography: Clinical and Economic Impact.
    Date
    Journal Radiology
    Excerpt

    PURPOSE: To evaluate the frequency and estimated costs of additional diagnostic workup for extracolonic findings detected at computed tomographic (CT) colonography in a large screening cohort. MATERIALS AND METHODS: This retrospective HIPAA-compliant study, which had institutional review board approval, evaluated extracolonic findings in 2195 consecutive asymptomatic adults (1199 women, 996 men; age range, 40-90 years; mean age, 58.0 years +/- 8.1 [standard deviation]) undergoing low-dose CT colonographic screening performed without contrast material at a single institution over a 20-month period. All diagnostic workups generated because of extracolonic findings were reviewed. Associated costs were estimated by using 2006 Medicare average reimbursement. Testing for statistical significance was performed by using the chi(2) and t tests. RESULTS: Further diagnostic workup for unsuspected extracolonic findings was performed in 133 (6.1%) of 2195 patients, including 18 patients in whom additional workup was not recommended by the radiologist. Additional testing included ultrasonography (n = 64), CT (n = 59), magnetic resonance imaging (n = 11), other diagnostic imaging tests (n = 19), nonsurgical invasive procedures (n = 19), and surgical procedures (n = 22). Benign findings were confirmed in the majority of cases, but relevant new diagnoses were made in 55 (2.5%) patients, including extracolonic malignancies in nine patients. The mean cost per patient for nonsurgical procedures was $31.02 (95% confidence interval: $23.72, $38.94); that for surgical procedures was $67.54 (95% confidence interval: $38.62, $101.55). CONCLUSION: Detection of relevant unsuspected extracolonic disease at CT colonographic screening is not rare, accounting for a relatively large percentage of cases in which additional workup was recommended. Judicious handling of potential extracolonic findings is warranted to balance the cost of additional workup against the potential for early detection of important disease, because many findings will prove to be of no clinical consequence.

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